new fix ti/spring command, remove fix ti/rs

Collected small changes and bugfixes

.gitignore

@@ -0,0 +1,34 @@
+*~
+*.o
+*.so
+*.cu_o
+*.ptx
+*_ptx.h
+*.a
+*.d
+*.x
+*.exe
+*.dll
+*.pyc
+__pycache__
+
+Obj_*
+log.lammps
+log.cite
+*.bz2
+*.gz
+*.tar
+.*.swp
+*.orig
+*.rej
+.vagrant
+\#*#
+.#*
+
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db

bench/log.15Feb16.chain.fixed.icc.1

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+LAMMPS (15 Feb 2016)
+# FENE beadspring benchmark
+
+units		lj
+atom_style	bond
+special_bonds   fene
+
+read_data	data.chain
+  orthogonal box = (-16.796 -16.796 -16.796) to (16.796 16.796 16.796)
+  1 by 1 by 1 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+  scanning bonds ...
+  1 = max bonds/atom
+  reading bonds ...
+  31680 bonds
+  2 = max # of 1-2 neighbors
+  2 = max # of special neighbors
+
+neighbor	0.4 bin
+neigh_modify	every 1 delay 1
+
+bond_style      fene
+bond_coeff	1 30.0 1.5 1.0 1.0
+
+pair_style	lj/cut 1.12
+pair_modify	shift yes
+pair_coeff	1 1 1.0 1.0 1.12
+
+fix		1 all nve
+fix		2 all langevin 1.0 1.0 10.0 904297
+
+thermo          100
+timestep	0.012
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 1 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 1.52
+  ghost atom cutoff = 1.52
+  binsize = 0.76 -> bins = 45 45 45
+Memory usage per processor = 11.5189 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0   0.97029772   0.44484087    20.494523    22.394765    4.6721833 
+     100    0.9729966    0.4361122    20.507698     22.40326    4.6548819 
+Loop time of 0.978585 on 1 procs for 100 steps with 32000 atoms
+
+Performance: 105948.895 tau/day, 102.188 timesteps/s
+100.0% CPU use with 1 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.19562    | 0.19562    | 0.19562    |   0.0 | 19.99
+Bond    | 0.087475   | 0.087475   | 0.087475   |   0.0 |  8.94
+Neigh   | 0.44861    | 0.44861    | 0.44861    |   0.0 | 45.84
+Comm    | 0.032932   | 0.032932   | 0.032932   |   0.0 |  3.37
+Output  | 0.00010395 | 0.00010395 | 0.00010395 |   0.0 |  0.01
+Modify  | 0.19413    | 0.19413    | 0.19413    |   0.0 | 19.84
+Other   |            | 0.01972    |            |       |  2.02
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Nghost:    9493 ave 9493 max 9493 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Neighs:    155873 ave 155873 max 155873 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+
+Total # of neighbors = 155873
+Ave neighs/atom = 4.87103
+Ave special neighs/atom = 1.98
+Neighbor list builds = 25
+Dangerous builds = 0
+Total wall time: 0:00:01

bench/log.15Feb16.chain.fixed.icc.4

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+LAMMPS (15 Feb 2016)
+# FENE beadspring benchmark
+
+units		lj
+atom_style	bond
+special_bonds   fene
+
+read_data	data.chain
+  orthogonal box = (-16.796 -16.796 -16.796) to (16.796 16.796 16.796)
+  1 by 2 by 2 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+  scanning bonds ...
+  1 = max bonds/atom
+  reading bonds ...
+  31680 bonds
+  2 = max # of 1-2 neighbors
+  2 = max # of special neighbors
+
+neighbor	0.4 bin
+neigh_modify	every 1 delay 1
+
+bond_style      fene
+bond_coeff	1 30.0 1.5 1.0 1.0
+
+pair_style	lj/cut 1.12
+pair_modify	shift yes
+pair_coeff	1 1 1.0 1.0 1.12
+
+fix		1 all nve
+fix		2 all langevin 1.0 1.0 10.0 904297
+
+thermo          100
+timestep	0.012
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 1 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 1.52
+  ghost atom cutoff = 1.52
+  binsize = 0.76 -> bins = 45 45 45
+Memory usage per processor = 3.91518 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0   0.97029772   0.44484087    20.494523    22.394765    4.6721833 
+     100   0.97145835   0.43803883    20.502691    22.397872     4.626988 
+Loop time of 0.271187 on 4 procs for 100 steps with 32000 atoms
+
+Performance: 382319.453 tau/day, 368.749 timesteps/s
+99.6% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.048621   | 0.050076   | 0.051229   |   0.4 | 18.47
+Bond    | 0.022254   | 0.022942   | 0.023567   |   0.3 |  8.46
+Neigh   | 0.11873    | 0.11881    | 0.11887    |   0.0 | 43.81
+Comm    | 0.019066   | 0.021357   | 0.024297   |   1.3 |  7.88
+Output  | 5.0068e-05 | 5.5015e-05 | 6.1035e-05 |   0.1 |  0.02
+Modify  | 0.048737   | 0.050198   | 0.051231   |   0.4 | 18.51
+Other   |            | 0.007751   |            |       |  2.86
+
+Nlocal:    8000 ave 8030 max 7974 min
+Histogram: 1 0 0 1 0 1 0 0 0 1
+Nghost:    4177 ave 4191 max 4160 min
+Histogram: 1 0 0 0 1 0 0 1 0 1
+Neighs:    38995.8 ave 39169 max 38852 min
+Histogram: 1 0 0 1 1 0 0 0 0 1
+
+Total # of neighbors = 155983
+Ave neighs/atom = 4.87447
+Ave special neighs/atom = 1.98
+Neighbor list builds = 25
+Dangerous builds = 0
+Total wall time: 0:00:00

bench/log.15Feb16.chain.scaled.icc.4

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+LAMMPS (15 Feb 2016)
+# FENE beadspring benchmark
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+units		lj
+atom_style	bond
+atom_modify	map hash
+special_bonds   fene
+
+read_data	data.chain
+  orthogonal box = (-16.796 -16.796 -16.796) to (16.796 16.796 16.796)
+  1 by 2 by 2 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+  scanning bonds ...
+  1 = max bonds/atom
+  reading bonds ...
+  31680 bonds
+  2 = max # of 1-2 neighbors
+  2 = max # of special neighbors
+
+replicate	$x $y $z
+replicate	2 $y $z
+replicate	2 2 $z
+replicate	2 2 1
+  orthogonal box = (-16.796 -16.796 -16.796) to (50.388 50.388 16.796)
+  2 by 2 by 1 MPI processor grid
+  128000 atoms
+  126720 bonds
+  2 = max # of 1-2 neighbors
+  2 = max # of special neighbors
+
+neighbor	0.4 bin
+neigh_modify	every 1 delay 1
+
+bond_style      fene
+bond_coeff	1 30.0 1.5 1.0 1.0
+
+pair_style	lj/cut 1.12
+pair_modify	shift yes
+pair_coeff	1 1 1.0 1.0 1.12
+
+fix		1 all nve
+fix		2 all langevin 1.0 1.0 10.0 904297
+
+thermo          100
+timestep	0.012
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 1 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 1.52
+  ghost atom cutoff = 1.52
+  binsize = 0.76 -> bins = 89 89 45
+Memory usage per processor = 12.8735 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0   0.97027498   0.44484087    20.494523    22.394765    4.6721833 
+     100   0.97682955   0.44239968    20.500229    22.407862    4.6527025 
+Loop time of 1.20889 on 4 procs for 100 steps with 128000 atoms
+
+Performance: 85764.410 tau/day, 82.720 timesteps/s
+99.8% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.21738    | 0.23306    | 0.23926    |   1.9 | 19.28
+Bond    | 0.094536   | 0.10196    | 0.10534    |   1.4 |  8.43
+Neigh   | 0.52311    | 0.52392    | 0.52519    |   0.1 | 43.34
+Comm    | 0.090161   | 0.10022    | 0.12557    |   4.7 |  8.29
+Output  | 0.00012207 | 0.00017327 | 0.00019598 |   0.2 |  0.01
+Modify  | 0.19662    | 0.20262    | 0.20672    |   0.8 | 16.76
+Other   |            | 0.04694    |            |       |  3.88
+
+Nlocal:    32000 ave 32015 max 31983 min
+Histogram: 1 0 1 0 0 0 0 0 1 1
+Nghost:    9492 ave 9522 max 9432 min
+Histogram: 1 0 0 0 0 0 1 0 0 2
+Neighs:    155837 ave 156079 max 155506 min
+Histogram: 1 0 0 0 0 1 0 0 1 1
+
+Total # of neighbors = 623349
+Ave neighs/atom = 4.86991
+Ave special neighs/atom = 1.98
+Neighbor list builds = 25
+Dangerous builds = 0
+Total wall time: 0:00:01

bench/log.15Feb16.chute.fixed.icc.1

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+LAMMPS (15 Feb 2016)
+# LAMMPS benchmark of granular flow
+# chute flow of 32000 atoms with frozen base at 26 degrees
+
+units		lj
+atom_style	sphere
+boundary	p p fs
+newton		off
+comm_modify	vel yes
+
+read_data	data.chute
+  orthogonal box = (0 0 0) to (40 20 37.2886)
+  1 by 1 by 1 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+
+pair_style	gran/hooke/history 200000.0 NULL 50.0 NULL 0.5 0
+pair_coeff	* *
+
+neighbor	0.1 bin
+neigh_modify	every 1 delay 0
+
+timestep	0.0001
+
+group		bottom type 2
+912 atoms in group bottom
+group		active subtract all bottom
+31088 atoms in group active
+neigh_modify	exclude group bottom bottom
+
+fix		1 all gravity 1.0 chute 26.0
+fix		2 bottom freeze
+fix		3 active nve/sphere
+
+compute		1 all erotate/sphere
+thermo_style	custom step atoms ke c_1 vol
+thermo_modify	norm no
+thermo		100
+
+run		100
+Neighbor list info ...
+  2 neighbor list requests
+  update every 1 steps, delay 0 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 1.1
+  ghost atom cutoff = 1.1
+  binsize = 0.55 -> bins = 73 37 68
+Memory usage per processor = 15.567 Mbytes
+Step Atoms KinEng 1 Volume 
+       0    32000    784139.13    1601.1263    29833.783 
+     100    32000    784292.08    1571.0968    29834.707 
+Loop time of 0.550482 on 1 procs for 100 steps with 32000 atoms
+
+Performance: 1569.534 tau/day, 181.659 timesteps/s
+100.1% CPU use with 1 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.33849    | 0.33849    | 0.33849    |   0.0 | 61.49
+Neigh   | 0.040353   | 0.040353   | 0.040353   |   0.0 |  7.33
+Comm    | 0.018023   | 0.018023   | 0.018023   |   0.0 |  3.27
+Output  | 0.00020385 | 0.00020385 | 0.00020385 |   0.0 |  0.04
+Modify  | 0.13155    | 0.13155    | 0.13155    |   0.0 | 23.90
+Other   |            | 0.02186    |            |       |  3.97
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Nghost:    5463 ave 5463 max 5463 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Neighs:    115133 ave 115133 max 115133 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+
+Total # of neighbors = 115133
+Ave neighs/atom = 3.59791
+Neighbor list builds = 2
+Dangerous builds = 0
+Total wall time: 0:00:00

bench/log.15Feb16.chute.fixed.icc.4

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+LAMMPS (15 Feb 2016)
+# LAMMPS benchmark of granular flow
+# chute flow of 32000 atoms with frozen base at 26 degrees
+
+units		lj
+atom_style	sphere
+boundary	p p fs
+newton		off
+comm_modify	vel yes
+
+read_data	data.chute
+  orthogonal box = (0 0 0) to (40 20 37.2886)
+  2 by 1 by 2 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+
+pair_style	gran/hooke/history 200000.0 NULL 50.0 NULL 0.5 0
+pair_coeff	* *
+
+neighbor	0.1 bin
+neigh_modify	every 1 delay 0
+
+timestep	0.0001
+
+group		bottom type 2
+912 atoms in group bottom
+group		active subtract all bottom
+31088 atoms in group active
+neigh_modify	exclude group bottom bottom
+
+fix		1 all gravity 1.0 chute 26.0
+fix		2 bottom freeze
+fix		3 active nve/sphere
+
+compute		1 all erotate/sphere
+thermo_style	custom step atoms ke c_1 vol
+thermo_modify	norm no
+thermo		100
+
+run		100
+Neighbor list info ...
+  2 neighbor list requests
+  update every 1 steps, delay 0 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 1.1
+  ghost atom cutoff = 1.1
+  binsize = 0.55 -> bins = 73 37 68
+Memory usage per processor = 6.81783 Mbytes
+Step Atoms KinEng 1 Volume 
+       0    32000    784139.13    1601.1263    29833.783 
+     100    32000    784292.08    1571.0968    29834.707 
+Loop time of 0.13141 on 4 procs for 100 steps with 32000 atoms
+
+Performance: 6574.833 tau/day, 760.976 timesteps/s
+99.3% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.062505   | 0.067      | 0.07152    |   1.5 | 50.99
+Neigh   | 0.010041   | 0.0101     | 0.010178   |   0.1 |  7.69
+Comm    | 0.012347   | 0.012895   | 0.013444   |   0.5 |  9.81
+Output  | 6.3896e-05 | 0.00010294 | 0.00014091 |   0.3 |  0.08
+Modify  | 0.031802   | 0.032348   | 0.032897   |   0.3 | 24.62
+Other   |            | 0.008965   |            |       |  6.82
+
+Nlocal:    8000 ave 8008 max 7992 min
+Histogram: 2 0 0 0 0 0 0 0 0 2
+Nghost:    2439 ave 2450 max 2428 min
+Histogram: 2 0 0 0 0 0 0 0 0 2
+Neighs:    29500.5 ave 30488 max 28513 min
+Histogram: 2 0 0 0 0 0 0 0 0 2
+
+Total # of neighbors = 118002
+Ave neighs/atom = 3.68756
+Neighbor list builds = 2
+Dangerous builds = 0
+Total wall time: 0:00:00

bench/log.15Feb16.chute.scaled.icc.4

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+LAMMPS (15 Feb 2016)
+# LAMMPS benchmark of granular flow
+# chute flow of 32000 atoms with frozen base at 26 degrees
+
+variable	x index 1
+variable	y index 1
+
+units		lj
+atom_style	sphere
+boundary	p p fs
+newton		off
+comm_modify	vel yes
+
+read_data	data.chute
+  orthogonal box = (0 0 0) to (40 20 37.2886)
+  2 by 1 by 2 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+
+replicate	$x $y 1
+replicate	2 $y 1
+replicate	2 2 1
+  orthogonal box = (0 0 0) to (80 40 37.2922)
+  2 by 2 by 1 MPI processor grid
+  128000 atoms
+
+pair_style	gran/hooke/history 200000.0 NULL 50.0 NULL 0.5 0
+pair_coeff	* *
+
+neighbor	0.1 bin
+neigh_modify	every 1 delay 0
+
+timestep	0.0001
+
+group		bottom type 2
+3648 atoms in group bottom
+group		active subtract all bottom
+124352 atoms in group active
+neigh_modify	exclude group bottom bottom
+
+fix		1 all gravity 1.0 chute 26.0
+fix		2 bottom freeze
+fix		3 active nve/sphere
+
+compute		1 all erotate/sphere
+thermo_style	custom step atoms ke c_1 vol
+thermo_modify	norm no
+thermo		100
+
+run		100
+Neighbor list info ...
+  2 neighbor list requests
+  update every 1 steps, delay 0 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 1.1
+  ghost atom cutoff = 1.1
+  binsize = 0.55 -> bins = 146 73 68
+Memory usage per processor = 15.7007 Mbytes
+Step Atoms KinEng 1 Volume 
+       0   128000    3136556.5    6404.5051    119335.13 
+     100   128000    3137168.3    6284.3873    119338.83 
+Loop time of 0.906913 on 4 procs for 100 steps with 128000 atoms
+
+Performance: 952.683 tau/day, 110.264 timesteps/s
+99.7% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.51454    | 0.53094    | 0.55381    |   2.0 | 58.54
+Neigh   | 0.042597   | 0.043726   | 0.045801   |   0.6 |  4.82
+Comm    | 0.063027   | 0.064657   | 0.067367   |   0.7 |  7.13
+Output  | 0.00024891 | 0.00059718 | 0.00086498 |   1.0 |  0.07
+Modify  | 0.16508    | 0.17656    | 0.1925     |   2.6 | 19.47
+Other   |            | 0.09043    |            |       |  9.97
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 4 0 0 0 0 0 0 0 0 0
+Nghost:    5463 ave 5463 max 5463 min
+Histogram: 4 0 0 0 0 0 0 0 0 0
+Neighs:    115133 ave 115133 max 115133 min
+Histogram: 4 0 0 0 0 0 0 0 0 0
+
+Total # of neighbors = 460532
+Ave neighs/atom = 3.59791
+Neighbor list builds = 2
+Dangerous builds = 0
+Total wall time: 0:00:01

bench/log.15Feb16.eam.fixed.icc.1

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+LAMMPS (15 Feb 2016)
+# bulk Cu lattice
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+variable	xx equal 20*$x
+variable	xx equal 20*1
+variable	yy equal 20*$y
+variable	yy equal 20*1
+variable	zz equal 20*$z
+variable	zz equal 20*1
+
+units		metal
+atom_style	atomic
+
+lattice		fcc 3.615
+Lattice spacing in x,y,z = 3.615 3.615 3.615
+region		box block 0 ${xx} 0 ${yy} 0 ${zz}
+region		box block 0 20 0 ${yy} 0 ${zz}
+region		box block 0 20 0 20 0 ${zz}
+region		box block 0 20 0 20 0 20
+create_box	1 box
+Created orthogonal box = (0 0 0) to (72.3 72.3 72.3)
+  1 by 1 by 1 MPI processor grid
+create_atoms	1 box
+Created 32000 atoms
+
+pair_style	eam
+pair_coeff	1 1 Cu_u3.eam
+Reading potential file Cu_u3.eam with DATE: 2007-06-11
+
+velocity	all create 1600.0 376847 loop geom
+
+neighbor	1.0 bin
+neigh_modify    every 1 delay 5 check yes
+
+fix		1 all nve
+
+timestep	0.005
+thermo		50
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 5 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 5.95
+  ghost atom cutoff = 5.95
+  binsize = 2.975 -> bins = 25 25 25
+Memory usage per processor = 10.2238 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0         1600      -113280            0   -106662.09    18703.573 
+      50    781.69049   -109873.35            0   -106640.13    52273.088 
+     100      801.832    -109957.3            0   -106640.77    51322.821 
+Loop time of 5.90097 on 1 procs for 100 steps with 32000 atoms
+
+Performance: 7.321 ns/day, 3.278 hours/ns, 16.946 timesteps/s
+99.9% CPU use with 1 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 5.2121     | 5.2121     | 5.2121     |   0.0 | 88.33
+Neigh   | 0.58212    | 0.58212    | 0.58212    |   0.0 |  9.86
+Comm    | 0.030392   | 0.030392   | 0.030392   |   0.0 |  0.52
+Output  | 0.00023389 | 0.00023389 | 0.00023389 |   0.0 |  0.00
+Modify  | 0.060871   | 0.060871   | 0.060871   |   0.0 |  1.03
+Other   |            | 0.01527    |            |       |  0.26
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Nghost:    19909 ave 19909 max 19909 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Neighs:    1.20778e+06 ave 1.20778e+06 max 1.20778e+06 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+
+Total # of neighbors = 1207784
+Ave neighs/atom = 37.7433
+Neighbor list builds = 13
+Dangerous builds = 0
+Total wall time: 0:00:06

bench/log.15Feb16.eam.fixed.icc.4

@@ -0,0 +1,83 @@
+LAMMPS (15 Feb 2016)
+# bulk Cu lattice
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+variable	xx equal 20*$x
+variable	xx equal 20*1
+variable	yy equal 20*$y
+variable	yy equal 20*1
+variable	zz equal 20*$z
+variable	zz equal 20*1
+
+units		metal
+atom_style	atomic
+
+lattice		fcc 3.615
+Lattice spacing in x,y,z = 3.615 3.615 3.615
+region		box block 0 ${xx} 0 ${yy} 0 ${zz}
+region		box block 0 20 0 ${yy} 0 ${zz}
+region		box block 0 20 0 20 0 ${zz}
+region		box block 0 20 0 20 0 20
+create_box	1 box
+Created orthogonal box = (0 0 0) to (72.3 72.3 72.3)
+  1 by 2 by 2 MPI processor grid
+create_atoms	1 box
+Created 32000 atoms
+
+pair_style	eam
+pair_coeff	1 1 Cu_u3.eam
+Reading potential file Cu_u3.eam with DATE: 2007-06-11
+
+velocity	all create 1600.0 376847 loop geom
+
+neighbor	1.0 bin
+neigh_modify    every 1 delay 5 check yes
+
+fix		1 all nve
+
+timestep	0.005
+thermo		50
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 5 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 5.95
+  ghost atom cutoff = 5.95
+  binsize = 2.975 -> bins = 25 25 25
+Memory usage per processor = 5.09629 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0         1600      -113280            0   -106662.09    18703.573 
+      50    781.69049   -109873.35            0   -106640.13    52273.088 
+     100      801.832    -109957.3            0   -106640.77    51322.821 
+Loop time of 1.58019 on 4 procs for 100 steps with 32000 atoms
+
+Performance: 27.338 ns/day, 0.878 hours/ns, 63.284 timesteps/s
+99.8% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 1.3617     | 1.366      | 1.3723     |   0.4 | 86.45
+Neigh   | 0.15123    | 0.15232    | 0.15374    |   0.2 |  9.64
+Comm    | 0.033429   | 0.041275   | 0.047066   |   2.7 |  2.61
+Output  | 0.00011301 | 0.0001573  | 0.000211   |   0.3 |  0.01
+Modify  | 0.014694   | 0.015085   | 0.015421   |   0.2 |  0.95
+Other   |            | 0.005342   |            |       |  0.34
+
+Nlocal:    8000 ave 8008 max 7993 min
+Histogram: 2 0 0 0 0 0 0 0 1 1
+Nghost:    9130.25 ave 9138 max 9122 min
+Histogram: 2 0 0 0 0 0 0 0 0 2
+Neighs:    301946 ave 302392 max 301360 min
+Histogram: 1 0 0 0 1 0 0 0 1 1
+
+Total # of neighbors = 1207784
+Ave neighs/atom = 37.7433
+Neighbor list builds = 13
+Dangerous builds = 0
+Total wall time: 0:00:01

bench/log.15Feb16.eam.scaled.icc.4

@@ -0,0 +1,83 @@
+LAMMPS (15 Feb 2016)
+# bulk Cu lattice
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+variable	xx equal 20*$x
+variable	xx equal 20*2
+variable	yy equal 20*$y
+variable	yy equal 20*2
+variable	zz equal 20*$z
+variable	zz equal 20*1
+
+units		metal
+atom_style	atomic
+
+lattice		fcc 3.615
+Lattice spacing in x,y,z = 3.615 3.615 3.615
+region		box block 0 ${xx} 0 ${yy} 0 ${zz}
+region		box block 0 40 0 ${yy} 0 ${zz}
+region		box block 0 40 0 40 0 ${zz}
+region		box block 0 40 0 40 0 20
+create_box	1 box
+Created orthogonal box = (0 0 0) to (144.6 144.6 72.3)
+  2 by 2 by 1 MPI processor grid
+create_atoms	1 box
+Created 128000 atoms
+
+pair_style	eam
+pair_coeff	1 1 Cu_u3.eam
+Reading potential file Cu_u3.eam with DATE: 2007-06-11
+
+velocity	all create 1600.0 376847 loop geom
+
+neighbor	1.0 bin
+neigh_modify    every 1 delay 5 check yes
+
+fix		1 all nve
+
+timestep	0.005
+thermo		50
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 5 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 5.95
+  ghost atom cutoff = 5.95
+  binsize = 2.975 -> bins = 49 49 25
+Memory usage per processor = 10.1402 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0         1600      -453120            0   -426647.73    18704.012 
+      50    779.50001   -439457.02            0   -426560.06    52355.276 
+     100    797.97828   -439764.76            0   -426562.07     51474.74 
+Loop time of 6.46849 on 4 procs for 100 steps with 128000 atoms
+
+Performance: 6.679 ns/day, 3.594 hours/ns, 15.460 timesteps/s
+99.9% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 5.581      | 5.5997     | 5.6265     |   0.8 | 86.57
+Neigh   | 0.65287    | 0.658      | 0.66374    |   0.5 | 10.17
+Comm    | 0.075706   | 0.11015    | 0.13655    |   7.2 |  1.70
+Output  | 0.00026488 | 0.00028312 | 0.00029302 |   0.1 |  0.00
+Modify  | 0.069607   | 0.072407   | 0.074555   |   0.7 |  1.12
+Other   |            | 0.02794    |            |       |  0.43
+
+Nlocal:    32000 ave 32092 max 31914 min
+Histogram: 1 0 0 1 0 1 0 0 0 1
+Nghost:    19910 ave 19997 max 19818 min
+Histogram: 1 0 0 0 1 0 1 0 0 1
+Neighs:    1.20728e+06 ave 1.21142e+06 max 1.2036e+06 min
+Histogram: 1 0 0 1 1 0 0 0 0 1
+
+Total # of neighbors = 4829126
+Ave neighs/atom = 37.7275
+Neighbor list builds = 14
+Dangerous builds = 0
+Total wall time: 0:00:06

bench/log.15Feb16.lj.fixed.icc.1

@@ -0,0 +1,79 @@
+LAMMPS (15 Feb 2016)
+# 3d Lennard-Jones melt
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+variable	xx equal 20*$x
+variable	xx equal 20*1
+variable	yy equal 20*$y
+variable	yy equal 20*1
+variable	zz equal 20*$z
+variable	zz equal 20*1
+
+units		lj
+atom_style	atomic
+
+lattice		fcc 0.8442
+Lattice spacing in x,y,z = 1.6796 1.6796 1.6796
+region		box block 0 ${xx} 0 ${yy} 0 ${zz}
+region		box block 0 20 0 ${yy} 0 ${zz}
+region		box block 0 20 0 20 0 ${zz}
+region		box block 0 20 0 20 0 20
+create_box	1 box
+Created orthogonal box = (0 0 0) to (33.5919 33.5919 33.5919)
+  1 by 1 by 1 MPI processor grid
+create_atoms	1 box
+Created 32000 atoms
+mass		1 1.0
+
+velocity	all create 1.44 87287 loop geom
+
+pair_style	lj/cut 2.5
+pair_coeff	1 1 1.0 1.0 2.5
+
+neighbor	0.3 bin
+neigh_modify	delay 0 every 20 check no
+
+fix		1 all nve
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 20 steps, delay 0 steps, check no
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 2.8
+  ghost atom cutoff = 2.8
+  binsize = 1.4 -> bins = 24 24 24
+Memory usage per processor = 8.21387 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0         1.44   -6.7733681            0   -4.6134356   -5.0197073 
+     100    0.7574531   -5.7585055            0   -4.6223613   0.20726105 
+Loop time of 2.26309 on 1 procs for 100 steps with 32000 atoms
+
+Performance: 19088.920 tau/day, 44.187 timesteps/s
+99.9% CPU use with 1 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 1.9341     | 1.9341     | 1.9341     |   0.0 | 85.46
+Neigh   | 0.2442     | 0.2442     | 0.2442     |   0.0 | 10.79
+Comm    | 0.024158   | 0.024158   | 0.024158   |   0.0 |  1.07
+Output  | 0.00011611 | 0.00011611 | 0.00011611 |   0.0 |  0.01
+Modify  | 0.053222   | 0.053222   | 0.053222   |   0.0 |  2.35
+Other   |            | 0.007258   |            |       |  0.32
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Nghost:    19657 ave 19657 max 19657 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Neighs:    1.20283e+06 ave 1.20283e+06 max 1.20283e+06 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+
+Total # of neighbors = 1202833
+Ave neighs/atom = 37.5885
+Neighbor list builds = 5
+Dangerous builds not checked
+Total wall time: 0:00:02

bench/log.15Feb16.lj.fixed.icc.4

@@ -0,0 +1,79 @@
+LAMMPS (15 Feb 2016)
+# 3d Lennard-Jones melt
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+variable	xx equal 20*$x
+variable	xx equal 20*1
+variable	yy equal 20*$y
+variable	yy equal 20*1
+variable	zz equal 20*$z
+variable	zz equal 20*1
+
+units		lj
+atom_style	atomic
+
+lattice		fcc 0.8442
+Lattice spacing in x,y,z = 1.6796 1.6796 1.6796
+region		box block 0 ${xx} 0 ${yy} 0 ${zz}
+region		box block 0 20 0 ${yy} 0 ${zz}
+region		box block 0 20 0 20 0 ${zz}
+region		box block 0 20 0 20 0 20
+create_box	1 box
+Created orthogonal box = (0 0 0) to (33.5919 33.5919 33.5919)
+  1 by 2 by 2 MPI processor grid
+create_atoms	1 box
+Created 32000 atoms
+mass		1 1.0
+
+velocity	all create 1.44 87287 loop geom
+
+pair_style	lj/cut 2.5
+pair_coeff	1 1 1.0 1.0 2.5
+
+neighbor	0.3 bin
+neigh_modify	delay 0 every 20 check no
+
+fix		1 all nve
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 20 steps, delay 0 steps, check no
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 2.8
+  ghost atom cutoff = 2.8
+  binsize = 1.4 -> bins = 24 24 24
+Memory usage per processor = 4.09506 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0         1.44   -6.7733681            0   -4.6134356   -5.0197073 
+     100    0.7574531   -5.7585055            0   -4.6223613   0.20726105 
+Loop time of 0.640733 on 4 procs for 100 steps with 32000 atoms
+
+Performance: 67422.779 tau/day, 156.071 timesteps/s
+99.7% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 0.49487    | 0.51733    | 0.5322     |   1.9 | 80.74
+Neigh   | 0.061131   | 0.063685   | 0.065433   |   0.6 |  9.94
+Comm    | 0.02457    | 0.042349   | 0.069598   |   8.1 |  6.61
+Output  | 5.9843e-05 | 6.3181e-05 | 6.6996e-05 |   0.0 |  0.01
+Modify  | 0.012961   | 0.013863   | 0.014491   |   0.5 |  2.16
+Other   |            | 0.003448   |            |       |  0.54
+
+Nlocal:    8000 ave 8037 max 7964 min
+Histogram: 2 0 0 0 0 0 0 0 1 1
+Nghost:    9007.5 ave 9050 max 8968 min
+Histogram: 1 1 0 0 0 0 0 1 0 1
+Neighs:    300708 ave 305113 max 297203 min
+Histogram: 1 0 0 1 1 0 0 0 0 1
+
+Total # of neighbors = 1202833
+Ave neighs/atom = 37.5885
+Neighbor list builds = 5
+Dangerous builds not checked
+Total wall time: 0:00:00

bench/log.15Feb16.lj.scaled.icc.4

@@ -0,0 +1,79 @@
+LAMMPS (15 Feb 2016)
+# 3d Lennard-Jones melt
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+variable	xx equal 20*$x
+variable	xx equal 20*2
+variable	yy equal 20*$y
+variable	yy equal 20*2
+variable	zz equal 20*$z
+variable	zz equal 20*1
+
+units		lj
+atom_style	atomic
+
+lattice		fcc 0.8442
+Lattice spacing in x,y,z = 1.6796 1.6796 1.6796
+region		box block 0 ${xx} 0 ${yy} 0 ${zz}
+region		box block 0 40 0 ${yy} 0 ${zz}
+region		box block 0 40 0 40 0 ${zz}
+region		box block 0 40 0 40 0 20
+create_box	1 box
+Created orthogonal box = (0 0 0) to (67.1838 67.1838 33.5919)
+  2 by 2 by 1 MPI processor grid
+create_atoms	1 box
+Created 128000 atoms
+mass		1 1.0
+
+velocity	all create 1.44 87287 loop geom
+
+pair_style	lj/cut 2.5
+pair_coeff	1 1 1.0 1.0 2.5
+
+neighbor	0.3 bin
+neigh_modify	delay 0 every 20 check no
+
+fix		1 all nve
+
+run		100
+Neighbor list info ...
+  1 neighbor list requests
+  update every 20 steps, delay 0 steps, check no
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 2.8
+  ghost atom cutoff = 2.8
+  binsize = 1.4 -> bins = 48 48 24
+Memory usage per processor = 8.13678 Mbytes
+Step Temp E_pair E_mol TotEng Press 
+       0         1.44   -6.7733681            0   -4.6133849   -5.0196788 
+     100   0.75841891    -5.759957            0   -4.6223375   0.20008866 
+Loop time of 2.57914 on 4 procs for 100 steps with 128000 atoms
+
+Performance: 16749.768 tau/day, 38.773 timesteps/s
+99.8% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 2.042      | 2.1092     | 2.1668     |   3.1 | 81.78
+Neigh   | 0.23982    | 0.24551    | 0.25233    |   1.0 |  9.52
+Comm    | 0.067088   | 0.13887    | 0.22681    |  15.7 |  5.38
+Output  | 0.00013185 | 0.00021666 | 0.00027108 |   0.4 |  0.01
+Modify  | 0.060348   | 0.071269   | 0.077063   |   2.5 |  2.76
+Other   |            | 0.01403    |            |       |  0.54
+
+Nlocal:    32000 ave 32060 max 31939 min
+Histogram: 1 0 1 0 0 0 0 1 0 1
+Nghost:    19630.8 ave 19681 max 19562 min
+Histogram: 1 0 0 0 1 0 0 0 1 1
+Neighs:    1.20195e+06 ave 1.20354e+06 max 1.19931e+06 min
+Histogram: 1 0 0 0 0 0 0 2 0 1
+
+Total # of neighbors = 4807797
+Ave neighs/atom = 37.5609
+Neighbor list builds = 5
+Dangerous builds not checked
+Total wall time: 0:00:02

bench/log.15Feb16.rhodo.fixed.icc.1

@@ -0,0 +1,121 @@
+LAMMPS (15 Feb 2016)
+# Rhodopsin model
+
+units           real
+neigh_modify    delay 5 every 1
+
+atom_style      full
+bond_style      harmonic
+angle_style     charmm
+dihedral_style  charmm
+improper_style  harmonic
+pair_style      lj/charmm/coul/long 8.0 10.0
+pair_modify     mix arithmetic
+kspace_style    pppm 1e-4
+
+read_data       data.rhodo
+  orthogonal box = (-27.5 -38.5 -36.3646) to (27.5 38.5 36.3615)
+  1 by 1 by 1 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+  scanning bonds ...
+  4 = max bonds/atom
+  scanning angles ...
+  8 = max angles/atom
+  scanning dihedrals ...
+  18 = max dihedrals/atom
+  scanning impropers ...
+  2 = max impropers/atom
+  reading bonds ...
+  27723 bonds
+  reading angles ...
+  40467 angles
+  reading dihedrals ...
+  56829 dihedrals
+  reading impropers ...
+  1034 impropers
+  4 = max # of 1-2 neighbors
+  12 = max # of 1-3 neighbors
+  24 = max # of 1-4 neighbors
+  26 = max # of special neighbors
+
+fix             1 all shake 0.0001 5 0 m 1.0 a 232
+  1617 = # of size 2 clusters
+  3633 = # of size 3 clusters
+  747 = # of size 4 clusters
+  4233 = # of frozen angles
+fix             2 all npt temp 300.0 300.0 100.0 		z 0.0 0.0 1000.0 mtk no pchain 0 tchain 1
+
+special_bonds   charmm
+
+thermo          50
+thermo_style    multi
+timestep        2.0
+
+run		100
+PPPM initialization ...
+  G vector (1/distance) = 0.248835
+  grid = 25 32 32
+  stencil order = 5
+  estimated absolute RMS force accuracy = 0.0355478
+  estimated relative force accuracy = 0.000107051
+  using double precision FFTs
+  3d grid and FFT values/proc = 41070 25600
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 5 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 12
+  ghost atom cutoff = 12
+  binsize = 6 -> bins = 10 13 13
+Memory usage per processor = 91.7487 Mbytes
+---------------- Step        0 ----- CPU =      0.0000 (sec) ----------------
+TotEng   =    -25356.2064 KinEng   =     21444.8313 Temp     =       299.0397 
+PotEng   =    -46801.0377 E_bond   =      2537.9940 E_angle  =     10921.3742 
+E_dihed  =      5211.7865 E_impro  =       213.5116 E_vdwl   =     -2307.8634 
+E_coul   =    207025.8927 E_long   =   -270403.7333 Press    =      -142.6035 
+Volume   =    307995.0335 
+---------------- Step       50 ----- CPU =     17.6362 (sec) ----------------
+TotEng   =    -25330.0828 KinEng   =     21501.0029 Temp     =       299.8230 
+PotEng   =    -46831.0857 E_bond   =      2471.7004 E_angle  =     10836.4975 
+E_dihed  =      5239.6299 E_impro  =       227.1218 E_vdwl   =     -1993.2754 
+E_coul   =    206797.6331 E_long   =   -270410.3930 Press    =       237.6701 
+Volume   =    308031.5639 
+---------------- Step      100 ----- CPU =     35.9089 (sec) ----------------
+TotEng   =    -25290.7593 KinEng   =     21592.0117 Temp     =       301.0920 
+PotEng   =    -46882.7709 E_bond   =      2567.9807 E_angle  =     10781.9408 
+E_dihed  =      5198.7432 E_impro  =       216.7834 E_vdwl   =     -1902.4783 
+E_coul   =    206659.2326 E_long   =   -270404.9733 Press    =         6.9960 
+Volume   =    308133.9888 
+Loop time of 35.9089 on 1 procs for 100 steps with 32000 atoms
+
+Performance: 0.481 ns/day, 49.874 hours/ns, 2.785 timesteps/s
+99.9% CPU use with 1 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 25.731     | 25.731     | 25.731     |   0.0 | 71.66
+Bond    | 1.2771     | 1.2771     | 1.2771     |   0.0 |  3.56
+Kspace  | 3.2094     | 3.2094     | 3.2094     |   0.0 |  8.94
+Neigh   | 4.4538     | 4.4538     | 4.4538     |   0.0 | 12.40
+Comm    | 0.068507   | 0.068507   | 0.068507   |   0.0 |  0.19
+Output  | 0.00025916 | 0.00025916 | 0.00025916 |   0.0 |  0.00
+Modify  | 1.1417     | 1.1417     | 1.1417     |   0.0 |  3.18
+Other   |            | 0.027      |            |       |  0.08
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Nghost:    47958 ave 47958 max 47958 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+Neighs:    1.20281e+07 ave 1.20281e+07 max 1.20281e+07 min
+Histogram: 1 0 0 0 0 0 0 0 0 0
+
+Total # of neighbors = 12028107
+Ave neighs/atom = 375.878
+Ave special neighs/atom = 7.43187
+Neighbor list builds = 11
+Dangerous builds = 0
+Total wall time: 0:00:37

bench/log.15Feb16.rhodo.fixed.icc.4

@@ -0,0 +1,121 @@
+LAMMPS (15 Feb 2016)
+# Rhodopsin model
+
+units           real
+neigh_modify    delay 5 every 1
+
+atom_style      full
+bond_style      harmonic
+angle_style     charmm
+dihedral_style  charmm
+improper_style  harmonic
+pair_style      lj/charmm/coul/long 8.0 10.0
+pair_modify     mix arithmetic
+kspace_style    pppm 1e-4
+
+read_data       data.rhodo
+  orthogonal box = (-27.5 -38.5 -36.3646) to (27.5 38.5 36.3615)
+  1 by 2 by 2 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+  scanning bonds ...
+  4 = max bonds/atom
+  scanning angles ...
+  8 = max angles/atom
+  scanning dihedrals ...
+  18 = max dihedrals/atom
+  scanning impropers ...
+  2 = max impropers/atom
+  reading bonds ...
+  27723 bonds
+  reading angles ...
+  40467 angles
+  reading dihedrals ...
+  56829 dihedrals
+  reading impropers ...
+  1034 impropers
+  4 = max # of 1-2 neighbors
+  12 = max # of 1-3 neighbors
+  24 = max # of 1-4 neighbors
+  26 = max # of special neighbors
+
+fix             1 all shake 0.0001 5 0 m 1.0 a 232
+  1617 = # of size 2 clusters
+  3633 = # of size 3 clusters
+  747 = # of size 4 clusters
+  4233 = # of frozen angles
+fix             2 all npt temp 300.0 300.0 100.0 		z 0.0 0.0 1000.0 mtk no pchain 0 tchain 1
+
+special_bonds   charmm
+
+thermo          50
+thermo_style    multi
+timestep        2.0
+
+run		100
+PPPM initialization ...
+  G vector (1/distance) = 0.248835
+  grid = 25 32 32
+  stencil order = 5
+  estimated absolute RMS force accuracy = 0.0355478
+  estimated relative force accuracy = 0.000107051
+  using double precision FFTs
+  3d grid and FFT values/proc = 13230 6400
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 5 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 12
+  ghost atom cutoff = 12
+  binsize = 6 -> bins = 10 13 13
+Memory usage per processor = 36.629 Mbytes
+---------------- Step        0 ----- CPU =      0.0000 (sec) ----------------
+TotEng   =    -25356.2064 KinEng   =     21444.8313 Temp     =       299.0397 
+PotEng   =    -46801.0377 E_bond   =      2537.9940 E_angle  =     10921.3742 
+E_dihed  =      5211.7865 E_impro  =       213.5116 E_vdwl   =     -2307.8634 
+E_coul   =    207025.8927 E_long   =   -270403.7333 Press    =      -142.6035 
+Volume   =    307995.0335 
+---------------- Step       50 ----- CPU =      4.7461 (sec) ----------------
+TotEng   =    -25330.0828 KinEng   =     21501.0029 Temp     =       299.8230 
+PotEng   =    -46831.0857 E_bond   =      2471.7004 E_angle  =     10836.4975 
+E_dihed  =      5239.6299 E_impro  =       227.1218 E_vdwl   =     -1993.2754 
+E_coul   =    206797.6331 E_long   =   -270410.3930 Press    =       237.6701 
+Volume   =    308031.5639 
+---------------- Step      100 ----- CPU =      9.6332 (sec) ----------------
+TotEng   =    -25290.7591 KinEng   =     21592.0117 Temp     =       301.0920 
+PotEng   =    -46882.7708 E_bond   =      2567.9807 E_angle  =     10781.9408 
+E_dihed  =      5198.7432 E_impro  =       216.7834 E_vdwl   =     -1902.4783 
+E_coul   =    206659.2327 E_long   =   -270404.9733 Press    =         6.9960 
+Volume   =    308133.9888 
+Loop time of 9.63322 on 4 procs for 100 steps with 32000 atoms
+
+Performance: 1.794 ns/day, 13.379 hours/ns, 10.381 timesteps/s
+99.9% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 6.4364     | 6.5993     | 6.7208     |   4.7 | 68.51
+Bond    | 0.30755    | 0.32435    | 0.35704    |   3.4 |  3.37
+Kspace  | 0.92248    | 1.0782     | 1.2597     |  13.0 | 11.19
+Neigh   | 1.1669     | 1.1672     | 1.1675     |   0.0 | 12.12
+Comm    | 0.094674   | 0.098065   | 0.10543    |   1.4 |  1.02
+Output  | 0.00015521 | 0.00016224 | 0.00018215 |   0.1 |  0.00
+Modify  | 0.32982    | 0.34654    | 0.35365    |   1.6 |  3.60
+Other   |            | 0.01943    |            |       |  0.20
+
+Nlocal:    8000 ave 8143 max 7933 min
+Histogram: 1 2 0 0 0 0 0 0 0 1
+Nghost:    22733.5 ave 22769 max 22693 min
+Histogram: 1 0 0 0 0 2 0 0 0 1
+Neighs:    3.00703e+06 ave 3.0975e+06 max 2.96493e+06 min
+Histogram: 1 2 0 0 0 0 0 0 0 1
+
+Total # of neighbors = 12028107
+Ave neighs/atom = 375.878
+Ave special neighs/atom = 7.43187
+Neighbor list builds = 11
+Dangerous builds = 0
+Total wall time: 0:00:10

bench/log.15Feb16.rhodo.scaled.icc.4

@@ -0,0 +1,142 @@
+LAMMPS (15 Feb 2016)
+# Rhodopsin model
+
+variable	x index 1
+variable	y index 1
+variable	z index 1
+
+units           real
+neigh_modify    delay 5 every 1
+
+atom_style      full
+atom_modify	map hash
+bond_style      harmonic
+angle_style     charmm
+dihedral_style  charmm
+improper_style  harmonic
+pair_style      lj/charmm/coul/long 8.0 10.0
+pair_modify     mix arithmetic
+kspace_style    pppm 1e-4
+
+read_data       data.rhodo
+  orthogonal box = (-27.5 -38.5 -36.3646) to (27.5 38.5 36.3615)
+  1 by 2 by 2 MPI processor grid
+  reading atoms ...
+  32000 atoms
+  reading velocities ...
+  32000 velocities
+  scanning bonds ...
+  4 = max bonds/atom
+  scanning angles ...
+  8 = max angles/atom
+  scanning dihedrals ...
+  18 = max dihedrals/atom
+  scanning impropers ...
+  2 = max impropers/atom
+  reading bonds ...
+  27723 bonds
+  reading angles ...
+  40467 angles
+  reading dihedrals ...
+  56829 dihedrals
+  reading impropers ...
+  1034 impropers
+  4 = max # of 1-2 neighbors
+  12 = max # of 1-3 neighbors
+  24 = max # of 1-4 neighbors
+  26 = max # of special neighbors
+
+replicate	$x $y $z
+replicate	2 $y $z
+replicate	2 2 $z
+replicate	2 2 1
+  orthogonal box = (-27.5 -38.5 -36.3646) to (82.5 115.5 36.3615)
+  2 by 2 by 1 MPI processor grid
+  128000 atoms
+  110892 bonds
+  161868 angles
+  227316 dihedrals
+  4136 impropers
+  4 = max # of 1-2 neighbors
+  12 = max # of 1-3 neighbors
+  24 = max # of 1-4 neighbors
+  26 = max # of special neighbors
+
+fix             1 all shake 0.0001 5 0 m 1.0 a 232
+  6468 = # of size 2 clusters
+  14532 = # of size 3 clusters
+  2988 = # of size 4 clusters
+  16932 = # of frozen angles
+fix             2 all npt temp 300.0 300.0 100.0 		z 0.0 0.0 1000.0 mtk no pchain 0 tchain 1
+
+special_bonds   charmm
+
+thermo          50
+thermo_style    multi
+timestep        2.0
+
+run		100
+PPPM initialization ...
+  G vector (1/distance) = 0.248593
+  grid = 48 60 36
+  stencil order = 5
+  estimated absolute RMS force accuracy = 0.0359793
+  estimated relative force accuracy = 0.00010835
+  using double precision FFTs
+  3d grid and FFT values/proc = 41615 25920
+Neighbor list info ...
+  1 neighbor list requests
+  update every 1 steps, delay 5 steps, check yes
+  max neighbors/atom: 2000, page size: 100000
+  master list distance cutoff = 12
+  ghost atom cutoff = 12
+  binsize = 6 -> bins = 19 26 13
+Memory usage per processor = 95.5339 Mbytes
+---------------- Step        0 ----- CPU =      0.0000 (sec) ----------------
+TotEng   =   -101425.4887 KinEng   =     85779.3251 Temp     =       299.0304 
+PotEng   =   -187204.8138 E_bond   =     10151.9760 E_angle  =     43685.4968 
+E_dihed  =     20847.1460 E_impro  =       854.0463 E_vdwl   =     -9231.4537 
+E_coul   =    827053.5824 E_long   =  -1080565.6077 Press    =      -142.3092 
+Volume   =   1231980.1340 
+---------------- Step       50 ----- CPU =     18.7806 (sec) ----------------
+TotEng   =   -101320.2677 KinEng   =     86003.4837 Temp     =       299.8118 
+PotEng   =   -187323.7514 E_bond   =      9887.1072 E_angle  =     43346.7922 
+E_dihed  =     20958.7032 E_impro  =       908.4715 E_vdwl   =     -7973.4457 
+E_coul   =    826141.3831 E_long   =  -1080592.7629 Press    =       238.0161 
+Volume   =   1232126.1855 
+---------------- Step      100 ----- CPU =     38.3684 (sec) ----------------
+TotEng   =   -101158.1849 KinEng   =     86355.6149 Temp     =       301.0393 
+PotEng   =   -187513.7998 E_bond   =     10272.0693 E_angle  =     43128.6454 
+E_dihed  =     20793.9759 E_impro  =       867.0826 E_vdwl   =     -7586.7186 
+E_coul   =    825583.7122 E_long   =  -1080572.5667 Press    =        15.2151 
+Volume   =   1232535.8423 
+Loop time of 38.3684 on 4 procs for 100 steps with 128000 atoms
+
+Performance: 0.450 ns/day, 53.289 hours/ns, 2.606 timesteps/s
+99.9% CPU use with 4 MPI tasks x no OpenMP threads
+
+MPI task timing breakdown:
+Section |  min time  |  avg time  |  max time  |%varavg| %total
+---------------------------------------------------------------
+Pair    | 26.205     | 26.538     | 26.911     |   5.0 | 69.17
+Bond    | 1.298      | 1.3125     | 1.3277     |   1.0 |  3.42
+Kspace  | 3.7099     | 4.0992     | 4.4422     |  13.3 | 10.68
+Neigh   | 4.6137     | 4.6144     | 4.615      |   0.0 | 12.03
+Comm    | 0.21398    | 0.21992    | 0.22886    |   1.2 |  0.57
+Output  | 0.00030518 | 0.00031543 | 0.00033307 |   0.1 |  0.00
+Modify  | 1.5066     | 1.5232     | 1.5388     |   1.0 |  3.97
+Other   |            | 0.06051    |            |       |  0.16
+
+Nlocal:    32000 ave 32000 max 32000 min
+Histogram: 4 0 0 0 0 0 0 0 0 0
+Nghost:    47957 ave 47957 max 47957 min
+Histogram: 4 0 0 0 0 0 0 0 0 0
+Neighs:    1.20281e+07 ave 1.20572e+07 max 1.1999e+07 min
+Histogram: 2 0 0 0 0 0 0 0 0 2
+
+Total # of neighbors = 48112472
+Ave neighs/atom = 375.879
+Ave special neighs/atom = 7.43187
+Neighbor list builds = 11
+Dangerous builds = 0
+Total wall time: 0:00:39

bench/log.15May15.chain.fixed.icc.1

@@ -1,67 +0,0 @@
-LAMMPS (30 Apr 2015)
-# FENE beadspring benchmark
-
-units		lj
-atom_style	bond
-special_bonds   fene
-
-read_data	data.chain
-  orthogonal box = (-16.796 -16.796 -16.796) to (16.796 16.796 16.796)
-  1 by 1 by 1 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-  scanning bonds ...
-  1 = max bonds/atom
-  reading bonds ...
-  31680 bonds
-  2 = max # of 1-2 neighbors
-  2 = max # of special neighbors
-
-neighbor	0.4 bin
-neigh_modify	every 1 delay 1
-
-bond_style      fene
-bond_coeff	1 30.0 1.5 1.0 1.0
-
-pair_style	lj/cut 1.12
-pair_modify	shift yes
-pair_coeff	1 1 1.0 1.0 1.12
-
-fix		1 all nve
-fix		2 all langevin 1.0 1.0 10.0 904297
-
-thermo          100
-timestep	0.012
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 1 steps, check yes
-  master list distance cutoff = 1.52
-Memory usage per processor = 11.5189 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0   0.97029772   0.44484087    20.494523    22.394765    4.6721833 
-     100    0.9729966    0.4361122    20.507698     22.40326    4.6548819 
-Loop time of 0.978717 on 1 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 0.195673 (19.9928)
-Bond  time (%) = 0.0878832 (8.97943)
-Neigh time (%) = 0.448004 (45.7746)
-Comm  time (%) = 0.0329976 (3.37152)
-Outpt time (%) = 0.000105143 (0.0107429)
-Other time (%) = 0.214054 (21.8709)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Nghost:    9493 ave 9493 max 9493 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Neighs:    155873 ave 155873 max 155873 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-
-Total # of neighbors = 155873
-Ave neighs/atom = 4.87103
-Ave special neighs/atom = 1.98
-Neighbor list builds = 25
-Dangerous builds = 0

bench/log.15May15.chain.fixed.icc.4

@@ -1,67 +0,0 @@
-LAMMPS (30 Apr 2015)
-# FENE beadspring benchmark
-
-units		lj
-atom_style	bond
-special_bonds   fene
-
-read_data	data.chain
-  orthogonal box = (-16.796 -16.796 -16.796) to (16.796 16.796 16.796)
-  1 by 2 by 2 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-  scanning bonds ...
-  1 = max bonds/atom
-  reading bonds ...
-  31680 bonds
-  2 = max # of 1-2 neighbors
-  2 = max # of special neighbors
-
-neighbor	0.4 bin
-neigh_modify	every 1 delay 1
-
-bond_style      fene
-bond_coeff	1 30.0 1.5 1.0 1.0
-
-pair_style	lj/cut 1.12
-pair_modify	shift yes
-pair_coeff	1 1 1.0 1.0 1.12
-
-fix		1 all nve
-fix		2 all langevin 1.0 1.0 10.0 904297
-
-thermo          100
-timestep	0.012
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 1 steps, check yes
-  master list distance cutoff = 1.52
-Memory usage per processor = 3.91518 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0   0.97029772   0.44484087    20.494523    22.394765    4.6721833 
-     100   0.97145835   0.43803883    20.502691    22.397872     4.626988 
-Loop time of 0.274371 on 4 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 0.0504887 (18.4016)
-Bond  time (%) = 0.0229129 (8.35106)
-Neigh time (%) = 0.119957 (43.7206)
-Comm  time (%) = 0.020835 (7.59373)
-Outpt time (%) = 5.74589e-05 (0.0209421)
-Other time (%) = 0.0601202 (21.912)
-
-Nlocal:    8000 ave 8030 max 7974 min
-Histogram: 1 0 0 1 0 1 0 0 0 1
-Nghost:    4177 ave 4191 max 4160 min
-Histogram: 1 0 0 0 1 0 0 1 0 1
-Neighs:    38995.8 ave 39169 max 38852 min
-Histogram: 1 0 0 1 1 0 0 0 0 1
-
-Total # of neighbors = 155983
-Ave neighs/atom = 4.87447
-Ave special neighs/atom = 1.98
-Neighbor list builds = 25
-Dangerous builds = 0

bench/log.15May15.chain.scaled.icc.4

@@ -1,83 +0,0 @@
-LAMMPS (30 Apr 2015)
-# FENE beadspring benchmark
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-units		lj
-atom_style	bond
-atom_modify	map hash
-special_bonds   fene
-
-read_data	data.chain
-  orthogonal box = (-16.796 -16.796 -16.796) to (16.796 16.796 16.796)
-  1 by 2 by 2 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-  scanning bonds ...
-  1 = max bonds/atom
-  reading bonds ...
-  31680 bonds
-  2 = max # of 1-2 neighbors
-  2 = max # of special neighbors
-
-replicate	$x $y $z
-replicate	2 $y $z
-replicate	2 2 $z
-replicate	2 2 1
-  orthogonal box = (-16.796 -16.796 -16.796) to (50.388 50.388 16.796)
-  2 by 2 by 1 MPI processor grid
-  128000 atoms
-  126720 bonds
-  2 = max # of 1-2 neighbors
-  2 = max # of special neighbors
-
-neighbor	0.4 bin
-neigh_modify	every 1 delay 1
-
-bond_style      fene
-bond_coeff	1 30.0 1.5 1.0 1.0
-
-pair_style	lj/cut 1.12
-pair_modify	shift yes
-pair_coeff	1 1 1.0 1.0 1.12
-
-fix		1 all nve
-fix		2 all langevin 1.0 1.0 10.0 904297
-
-thermo          100
-timestep	0.012
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 1 steps, check yes
-  master list distance cutoff = 1.52
-Memory usage per processor = 12.8735 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0   0.97027498   0.44484087    20.494523    22.394765    4.6721833 
-     100   0.97682955   0.44239968    20.500229    22.407862    4.6527025 
-Loop time of 1.19919 on 4 procs for 100 steps with 128000 atoms
-
-Pair  time (%) = 0.227794 (18.9957)
-Bond  time (%) = 0.0981662 (8.18606)
-Neigh time (%) = 0.527868 (44.0188)
-Comm  time (%) = 0.0980042 (8.17255)
-Outpt time (%) = 0.000200272 (0.0167006)
-Other time (%) = 0.247155 (20.6102)
-
-Nlocal:    32000 ave 32015 max 31983 min
-Histogram: 1 0 1 0 0 0 0 0 1 1
-Nghost:    9492 ave 9522 max 9432 min
-Histogram: 1 0 0 0 0 0 1 0 0 2
-Neighs:    155837 ave 156079 max 155506 min
-Histogram: 1 0 0 0 0 1 0 0 1 1
-
-Total # of neighbors = 623349
-Ave neighs/atom = 4.86991
-Ave special neighs/atom = 1.98
-Neighbor list builds = 25
-Dangerous builds = 0

bench/log.15May15.chute.fixed.icc.1

@@ -1,69 +0,0 @@
-LAMMPS (30 Apr 2015)
-# LAMMPS benchmark of granular flow
-# chute flow of 32000 atoms with frozen base at 26 degrees
-
-units		lj
-atom_style	sphere
-boundary	p p fs
-newton		off
-comm_modify	vel yes
-
-read_data	data.chute
-  orthogonal box = (0 0 0) to (40 20 37.2886)
-  1 by 1 by 1 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-
-pair_style	gran/hooke/history 200000.0 NULL 50.0 NULL 0.5 0
-pair_coeff	* *
-
-neighbor	0.1 bin
-neigh_modify	every 1 delay 0
-
-timestep	0.0001
-
-group		bottom type 2
-912 atoms in group bottom
-group		active subtract all bottom
-31088 atoms in group active
-neigh_modify	exclude group bottom bottom
-
-fix		1 all gravity 1.0 chute 26.0
-fix		2 bottom freeze
-fix		3 active nve/sphere
-
-compute		1 all erotate/sphere
-thermo_style	custom step atoms ke c_1 vol
-thermo_modify	norm no
-thermo		100
-
-run		100
-Neighbor list info ...
-  2 neighbor list requests
-  update every 1 steps, delay 0 steps, check yes
-  master list distance cutoff = 1.1
-Memory usage per processor = 15.567 Mbytes
-Step Atoms KinEng 1 Volume 
-       0    32000    784139.13    1601.1263    29833.783 
-     100    32000    784292.08    1571.0968    29834.707 
-Loop time of 0.539647 on 1 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 0.328789 (60.9267)
-Neigh time (%) = 0.0401711 (7.44397)
-Comm  time (%) = 0.0179052 (3.31795)
-Outpt time (%) = 0.00019908 (0.0368907)
-Other time (%) = 0.152582 (28.2745)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Nghost:    5463 ave 5463 max 5463 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Neighs:    115133 ave 115133 max 115133 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-
-Total # of neighbors = 115133
-Ave neighs/atom = 3.59791
-Neighbor list builds = 2
-Dangerous builds = 0

bench/log.15May15.chute.fixed.icc.4

@@ -1,69 +0,0 @@
-LAMMPS (30 Apr 2015)
-# LAMMPS benchmark of granular flow
-# chute flow of 32000 atoms with frozen base at 26 degrees
-
-units		lj
-atom_style	sphere
-boundary	p p fs
-newton		off
-comm_modify	vel yes
-
-read_data	data.chute
-  orthogonal box = (0 0 0) to (40 20 37.2886)
-  2 by 1 by 2 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-
-pair_style	gran/hooke/history 200000.0 NULL 50.0 NULL 0.5 0
-pair_coeff	* *
-
-neighbor	0.1 bin
-neigh_modify	every 1 delay 0
-
-timestep	0.0001
-
-group		bottom type 2
-912 atoms in group bottom
-group		active subtract all bottom
-31088 atoms in group active
-neigh_modify	exclude group bottom bottom
-
-fix		1 all gravity 1.0 chute 26.0
-fix		2 bottom freeze
-fix		3 active nve/sphere
-
-compute		1 all erotate/sphere
-thermo_style	custom step atoms ke c_1 vol
-thermo_modify	norm no
-thermo		100
-
-run		100
-Neighbor list info ...
-  2 neighbor list requests
-  update every 1 steps, delay 0 steps, check yes
-  master list distance cutoff = 1.1
-Memory usage per processor = 6.81783 Mbytes
-Step Atoms KinEng 1 Volume 
-       0    32000    784139.13    1601.1263    29833.783 
-     100    32000    784292.08    1571.0968    29834.707 
-Loop time of 0.146584 on 4 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 0.0737562 (50.3167)
-Neigh time (%) = 0.0105147 (7.17314)
-Comm  time (%) = 0.0147474 (10.0607)
-Outpt time (%) = 0.000131965 (0.0900267)
-Other time (%) = 0.0474337 (32.3594)
-
-Nlocal:    8000 ave 8008 max 7992 min
-Histogram: 2 0 0 0 0 0 0 0 0 2
-Nghost:    2439 ave 2450 max 2428 min
-Histogram: 2 0 0 0 0 0 0 0 0 2
-Neighs:    29500.5 ave 30488 max 28513 min
-Histogram: 2 0 0 0 0 0 0 0 0 2
-
-Total # of neighbors = 118002
-Ave neighs/atom = 3.68756
-Neighbor list builds = 2
-Dangerous builds = 0

bench/log.15May15.chute.scaled.icc.4

@@ -1,79 +0,0 @@
-LAMMPS (30 Apr 2015)
-# LAMMPS benchmark of granular flow
-# chute flow of 32000 atoms with frozen base at 26 degrees
-
-variable	x index 1
-variable	y index 1
-
-units		lj
-atom_style	sphere
-boundary	p p fs
-newton		off
-comm_modify	vel yes
-
-read_data	data.chute
-  orthogonal box = (0 0 0) to (40 20 37.2886)
-  2 by 1 by 2 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-
-replicate	$x $y 1
-replicate	2 $y 1
-replicate	2 2 1
-  orthogonal box = (0 0 0) to (80 40 37.2922)
-  2 by 2 by 1 MPI processor grid
-  128000 atoms
-
-pair_style	gran/hooke/history 200000.0 NULL 50.0 NULL 0.5 0
-pair_coeff	* *
-
-neighbor	0.1 bin
-neigh_modify	every 1 delay 0
-
-timestep	0.0001
-
-group		bottom type 2
-3648 atoms in group bottom
-group		active subtract all bottom
-124352 atoms in group active
-neigh_modify	exclude group bottom bottom
-
-fix		1 all gravity 1.0 chute 26.0
-fix		2 bottom freeze
-fix		3 active nve/sphere
-
-compute		1 all erotate/sphere
-thermo_style	custom step atoms ke c_1 vol
-thermo_modify	norm no
-thermo		100
-
-run		100
-Neighbor list info ...
-  2 neighbor list requests
-  update every 1 steps, delay 0 steps, check yes
-  master list distance cutoff = 1.1
-Memory usage per processor = 15.7007 Mbytes
-Step Atoms KinEng 1 Volume 
-       0   128000    3136556.5    6404.5051    119335.13 
-     100   128000    3137168.3    6284.3873    119338.83 
-Loop time of 0.899154 on 4 procs for 100 steps with 128000 atoms
-
-Pair  time (%) = 0.523338 (58.2033)
-Neigh time (%) = 0.0433982 (4.82656)
-Comm  time (%) = 0.0642623 (7.14697)
-Outpt time (%) = 0.000541449 (0.0602175)
-Other time (%) = 0.267615 (29.7629)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 4 0 0 0 0 0 0 0 0 0
-Nghost:    5463 ave 5463 max 5463 min
-Histogram: 4 0 0 0 0 0 0 0 0 0
-Neighs:    115133 ave 115133 max 115133 min
-Histogram: 4 0 0 0 0 0 0 0 0 0
-
-Total # of neighbors = 460532
-Ave neighs/atom = 3.59791
-Neighbor list builds = 2
-Dangerous builds = 0

bench/log.15May15.eam.fixed.icc.1

@@ -1,71 +0,0 @@
-LAMMPS (30 Apr 2015)
-# bulk Cu lattice
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-variable	xx equal 20*$x
-variable	xx equal 20*1
-variable	yy equal 20*$y
-variable	yy equal 20*1
-variable	zz equal 20*$z
-variable	zz equal 20*1
-
-units		metal
-atom_style	atomic
-
-lattice		fcc 3.615
-Lattice spacing in x,y,z = 3.615 3.615 3.615
-region		box block 0 ${xx} 0 ${yy} 0 ${zz}
-region		box block 0 20 0 ${yy} 0 ${zz}
-region		box block 0 20 0 20 0 ${zz}
-region		box block 0 20 0 20 0 20
-create_box	1 box
-Created orthogonal box = (0 0 0) to (72.3 72.3 72.3)
-  1 by 1 by 1 MPI processor grid
-create_atoms	1 box
-Created 32000 atoms
-
-pair_style	eam
-pair_coeff	1 1 Cu_u3.eam
-
-velocity	all create 1600.0 376847 loop geom
-
-neighbor	1.0 bin
-neigh_modify    every 1 delay 5 check yes
-
-fix		1 all nve
-
-timestep	0.005
-thermo		50
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 5 steps, check yes
-  master list distance cutoff = 5.95
-Memory usage per processor = 10.2238 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0         1600      -113280            0   -106662.09    18703.573 
-      50    781.69049   -109873.35            0   -106640.13    52273.088 
-     100      801.832    -109957.3            0   -106640.77    51322.821 
-Loop time of 5.89995 on 1 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 5.21525 (88.3948)
-Neigh time (%) = 0.579447 (9.82122)
-Comm  time (%) = 0.0302751 (0.513142)
-Outpt time (%) = 0.000234127 (0.00396829)
-Other time (%) = 0.0747423 (1.26683)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Nghost:    19909 ave 19909 max 19909 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Neighs:    1.20778e+06 ave 1.20778e+06 max 1.20778e+06 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-
-Total # of neighbors = 1207784
-Ave neighs/atom = 37.7433
-Neighbor list builds = 13
-Dangerous builds = 0

bench/log.15May15.eam.fixed.icc.4

@@ -1,71 +0,0 @@
-LAMMPS (30 Apr 2015)
-# bulk Cu lattice
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-variable	xx equal 20*$x
-variable	xx equal 20*1
-variable	yy equal 20*$y
-variable	yy equal 20*1
-variable	zz equal 20*$z
-variable	zz equal 20*1
-
-units		metal
-atom_style	atomic
-
-lattice		fcc 3.615
-Lattice spacing in x,y,z = 3.615 3.615 3.615
-region		box block 0 ${xx} 0 ${yy} 0 ${zz}
-region		box block 0 20 0 ${yy} 0 ${zz}
-region		box block 0 20 0 20 0 ${zz}
-region		box block 0 20 0 20 0 20
-create_box	1 box
-Created orthogonal box = (0 0 0) to (72.3 72.3 72.3)
-  1 by 2 by 2 MPI processor grid
-create_atoms	1 box
-Created 32000 atoms
-
-pair_style	eam
-pair_coeff	1 1 Cu_u3.eam
-
-velocity	all create 1600.0 376847 loop geom
-
-neighbor	1.0 bin
-neigh_modify    every 1 delay 5 check yes
-
-fix		1 all nve
-
-timestep	0.005
-thermo		50
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 5 steps, check yes
-  master list distance cutoff = 5.95
-Memory usage per processor = 5.09629 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0         1600      -113280            0   -106662.09    18703.573 
-      50    781.69049   -109873.35            0   -106640.13    52273.088 
-     100      801.832    -109957.3            0   -106640.77    51322.821 
-Loop time of 1.57597 on 4 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 1.36786 (86.7953)
-Neigh time (%) = 0.152391 (9.6697)
-Comm  time (%) = 0.0353726 (2.2445)
-Outpt time (%) = 0.000111699 (0.00708766)
-Other time (%) = 0.0202255 (1.28337)
-
-Nlocal:    8000 ave 8008 max 7993 min
-Histogram: 2 0 0 0 0 0 0 0 1 1
-Nghost:    9130.25 ave 9138 max 9122 min
-Histogram: 2 0 0 0 0 0 0 0 0 2
-Neighs:    301946 ave 302392 max 301360 min
-Histogram: 1 0 0 0 1 0 0 0 1 1
-
-Total # of neighbors = 1207784
-Ave neighs/atom = 37.7433
-Neighbor list builds = 13
-Dangerous builds = 0

bench/log.15May15.eam.scaled.icc.4

@@ -1,71 +0,0 @@
-LAMMPS (30 Apr 2015)
-# bulk Cu lattice
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-variable	xx equal 20*$x
-variable	xx equal 20*2
-variable	yy equal 20*$y
-variable	yy equal 20*2
-variable	zz equal 20*$z
-variable	zz equal 20*1
-
-units		metal
-atom_style	atomic
-
-lattice		fcc 3.615
-Lattice spacing in x,y,z = 3.615 3.615 3.615
-region		box block 0 ${xx} 0 ${yy} 0 ${zz}
-region		box block 0 40 0 ${yy} 0 ${zz}
-region		box block 0 40 0 40 0 ${zz}
-region		box block 0 40 0 40 0 20
-create_box	1 box
-Created orthogonal box = (0 0 0) to (144.6 144.6 72.3)
-  2 by 2 by 1 MPI processor grid
-create_atoms	1 box
-Created 128000 atoms
-
-pair_style	eam
-pair_coeff	1 1 Cu_u3.eam
-
-velocity	all create 1600.0 376847 loop geom
-
-neighbor	1.0 bin
-neigh_modify    every 1 delay 5 check yes
-
-fix		1 all nve
-
-timestep	0.005
-thermo		50
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 5 steps, check yes
-  master list distance cutoff = 5.95
-Memory usage per processor = 10.1402 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0         1600      -453120            0   -426647.73    18704.012 
-      50    779.50001   -439457.02            0   -426560.06    52355.276 
-     100    797.97828   -439764.76            0   -426562.07     51474.74 
-Loop time of 6.4972 on 4 procs for 100 steps with 128000 atoms
-
-Pair  time (%) = 5.61297 (86.3906)
-Neigh time (%) = 0.655333 (10.0864)
-Comm  time (%) = 0.130434 (2.00755)
-Outpt time (%) = 0.000279069 (0.00429522)
-Other time (%) = 0.0981811 (1.51113)
-
-Nlocal:    32000 ave 32092 max 31914 min
-Histogram: 1 0 0 1 0 1 0 0 0 1
-Nghost:    19910 ave 19997 max 19818 min
-Histogram: 1 0 0 0 1 0 1 0 0 1
-Neighs:    1.20728e+06 ave 1.21142e+06 max 1.2036e+06 min
-Histogram: 1 0 0 1 1 0 0 0 0 1
-
-Total # of neighbors = 4829126
-Ave neighs/atom = 37.7275
-Neighbor list builds = 14
-Dangerous builds = 0

bench/log.15May15.lj.fixed.icc.1

@@ -1,68 +0,0 @@
-LAMMPS (30 Apr 2015)
-# 3d Lennard-Jones melt
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-variable	xx equal 20*$x
-variable	xx equal 20*1
-variable	yy equal 20*$y
-variable	yy equal 20*1
-variable	zz equal 20*$z
-variable	zz equal 20*1
-
-units		lj
-atom_style	atomic
-
-lattice		fcc 0.8442
-Lattice spacing in x,y,z = 1.6796 1.6796 1.6796
-region		box block 0 ${xx} 0 ${yy} 0 ${zz}
-region		box block 0 20 0 ${yy} 0 ${zz}
-region		box block 0 20 0 20 0 ${zz}
-region		box block 0 20 0 20 0 20
-create_box	1 box
-Created orthogonal box = (0 0 0) to (33.5919 33.5919 33.5919)
-  1 by 1 by 1 MPI processor grid
-create_atoms	1 box
-Created 32000 atoms
-mass		1 1.0
-
-velocity	all create 1.44 87287 loop geom
-
-pair_style	lj/cut 2.5
-pair_coeff	1 1 1.0 1.0 2.5
-
-neighbor	0.3 bin
-neigh_modify	delay 0 every 20 check no
-
-fix		1 all nve
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 20 steps, delay 0 steps, check no
-  master list distance cutoff = 2.8
-Memory usage per processor = 8.21387 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0         1.44   -6.7733681            0   -4.6134356   -5.0197073 
-     100    0.7574531   -5.7585055            0   -4.6223613   0.20726105 
-Loop time of 2.25588 on 1 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 1.93512 (85.7815)
-Neigh time (%) = 0.236483 (10.483)
-Comm  time (%) = 0.0239627 (1.06224)
-Outpt time (%) = 0.000118017 (0.00523155)
-Other time (%) = 0.0601869 (2.66801)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Nghost:    19657 ave 19657 max 19657 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Neighs:    1.20283e+06 ave 1.20283e+06 max 1.20283e+06 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-
-Total # of neighbors = 1202833
-Ave neighs/atom = 37.5885
-Neighbor list builds = 5
-Dangerous builds = 0

bench/log.15May15.lj.fixed.icc.4

@@ -1,68 +0,0 @@
-LAMMPS (30 Apr 2015)
-# 3d Lennard-Jones melt
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-variable	xx equal 20*$x
-variable	xx equal 20*1
-variable	yy equal 20*$y
-variable	yy equal 20*1
-variable	zz equal 20*$z
-variable	zz equal 20*1
-
-units		lj
-atom_style	atomic
-
-lattice		fcc 0.8442
-Lattice spacing in x,y,z = 1.6796 1.6796 1.6796
-region		box block 0 ${xx} 0 ${yy} 0 ${zz}
-region		box block 0 20 0 ${yy} 0 ${zz}
-region		box block 0 20 0 20 0 ${zz}
-region		box block 0 20 0 20 0 20
-create_box	1 box
-Created orthogonal box = (0 0 0) to (33.5919 33.5919 33.5919)
-  1 by 2 by 2 MPI processor grid
-create_atoms	1 box
-Created 32000 atoms
-mass		1 1.0
-
-velocity	all create 1.44 87287 loop geom
-
-pair_style	lj/cut 2.5
-pair_coeff	1 1 1.0 1.0 2.5
-
-neighbor	0.3 bin
-neigh_modify	delay 0 every 20 check no
-
-fix		1 all nve
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 20 steps, delay 0 steps, check no
-  master list distance cutoff = 2.8
-Memory usage per processor = 4.09506 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0         1.44   -6.7733681            0   -4.6134356   -5.0197073 
-     100    0.7574531   -5.7585055            0   -4.6223613   0.20726105 
-Loop time of 0.623887 on 4 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 0.50691 (81.2504)
-Neigh time (%) = 0.0619052 (9.92251)
-Comm  time (%) = 0.0389298 (6.23989)
-Outpt time (%) = 5.85914e-05 (0.00939135)
-Other time (%) = 0.0160829 (2.57785)
-
-Nlocal:    8000 ave 8037 max 7964 min
-Histogram: 2 0 0 0 0 0 0 0 1 1
-Nghost:    9007.5 ave 9050 max 8968 min
-Histogram: 1 1 0 0 0 0 0 1 0 1
-Neighs:    300708 ave 305113 max 297203 min
-Histogram: 1 0 0 1 1 0 0 0 0 1
-
-Total # of neighbors = 1202833
-Ave neighs/atom = 37.5885
-Neighbor list builds = 5
-Dangerous builds = 0

bench/log.15May15.lj.scaled.icc.4

@@ -1,68 +0,0 @@
-LAMMPS (30 Apr 2015)
-# 3d Lennard-Jones melt
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-variable	xx equal 20*$x
-variable	xx equal 20*2
-variable	yy equal 20*$y
-variable	yy equal 20*2
-variable	zz equal 20*$z
-variable	zz equal 20*1
-
-units		lj
-atom_style	atomic
-
-lattice		fcc 0.8442
-Lattice spacing in x,y,z = 1.6796 1.6796 1.6796
-region		box block 0 ${xx} 0 ${yy} 0 ${zz}
-region		box block 0 40 0 ${yy} 0 ${zz}
-region		box block 0 40 0 40 0 ${zz}
-region		box block 0 40 0 40 0 20
-create_box	1 box
-Created orthogonal box = (0 0 0) to (67.1838 67.1838 33.5919)
-  2 by 2 by 1 MPI processor grid
-create_atoms	1 box
-Created 128000 atoms
-mass		1 1.0
-
-velocity	all create 1.44 87287 loop geom
-
-pair_style	lj/cut 2.5
-pair_coeff	1 1 1.0 1.0 2.5
-
-neighbor	0.3 bin
-neigh_modify	delay 0 every 20 check no
-
-fix		1 all nve
-
-run		100
-Neighbor list info ...
-  1 neighbor list requests
-  update every 20 steps, delay 0 steps, check no
-  master list distance cutoff = 2.8
-Memory usage per processor = 8.13678 Mbytes
-Step Temp E_pair E_mol TotEng Press 
-       0         1.44   -6.7733681            0   -4.6133849   -5.0196788 
-     100   0.75841891    -5.759957            0   -4.6223375   0.20008866 
-Loop time of 2.53011 on 4 procs for 100 steps with 128000 atoms
-
-Pair  time (%) = 2.09024 (82.6146)
-Neigh time (%) = 0.24414 (9.64939)
-Comm  time (%) = 0.111739 (4.41638)
-Outpt time (%) = 0.000135601 (0.00535947)
-Other time (%) = 0.0838551 (3.31428)
-
-Nlocal:    32000 ave 32060 max 31939 min
-Histogram: 1 0 1 0 0 0 0 1 0 1
-Nghost:    19630.8 ave 19681 max 19562 min
-Histogram: 1 0 0 0 1 0 0 0 1 1
-Neighs:    1.20195e+06 ave 1.20354e+06 max 1.19931e+06 min
-Histogram: 1 0 0 0 0 0 0 2 0 1
-
-Total # of neighbors = 4807797
-Ave neighs/atom = 37.5609
-Neighbor list builds = 5
-Dangerous builds = 0

bench/log.15May15.rhodo.fixed.icc.1

@@ -1,110 +0,0 @@
-LAMMPS (30 Apr 2015)
-# Rhodopsin model
-
-units           real
-neigh_modify    delay 5 every 1
-
-atom_style      full
-bond_style      harmonic
-angle_style     charmm
-dihedral_style  charmm
-improper_style  harmonic
-pair_style      lj/charmm/coul/long 8.0 10.0
-pair_modify     mix arithmetic
-kspace_style    pppm 1e-4
-
-read_data       data.rhodo
-  orthogonal box = (-27.5 -38.5 -36.3646) to (27.5 38.5 36.3615)
-  1 by 1 by 1 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-  scanning bonds ...
-  4 = max bonds/atom
-  scanning angles ...
-  8 = max angles/atom
-  scanning dihedrals ...
-  18 = max dihedrals/atom
-  scanning impropers ...
-  2 = max impropers/atom
-  reading bonds ...
-  27723 bonds
-  reading angles ...
-  40467 angles
-  reading dihedrals ...
-  56829 dihedrals
-  reading impropers ...
-  1034 impropers
-  4 = max # of 1-2 neighbors
-  12 = max # of 1-3 neighbors
-  24 = max # of 1-4 neighbors
-  26 = max # of special neighbors
-
-fix             1 all shake 0.0001 5 0 m 1.0 a 232
-  1617 = # of size 2 clusters
-  3633 = # of size 3 clusters
-  747 = # of size 4 clusters
-  4233 = # of frozen angles
-fix             2 all npt temp 300.0 300.0 100.0 		z 0.0 0.0 1000.0 mtk no pchain 0 tchain 1
-
-special_bonds   charmm
-
-thermo          50
-thermo_style    multi
-timestep        2.0
-
-run		100
-PPPM initialization ...
-  G vector (1/distance) = 0.248835
-  grid = 25 32 32
-  stencil order = 5
-  estimated absolute RMS force accuracy = 0.0355478
-  estimated relative force accuracy = 0.000107051
-  using double precision FFTs
-  3d grid and FFT values/proc = 41070 25600
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 5 steps, check yes
-  master list distance cutoff = 12
-Memory usage per processor = 91.7487 Mbytes
----------------- Step        0 ----- CPU =      0.0000 (sec) ----------------
-TotEng   =    -25356.2064 KinEng   =     21444.8313 Temp     =       299.0397 
-PotEng   =    -46801.0377 E_bond   =      2537.9940 E_angle  =     10921.3742 
-E_dihed  =      5211.7865 E_impro  =       213.5116 E_vdwl   =     -2307.8634 
-E_coul   =    207025.8927 E_long   =   -270403.7333 Press    =      -142.6035 
-Volume   =    307995.0335 
----------------- Step       50 ----- CPU =     17.3751 (sec) ----------------
-TotEng   =    -25330.0828 KinEng   =     21501.0029 Temp     =       299.8230 
-PotEng   =    -46831.0857 E_bond   =      2471.7004 E_angle  =     10836.4975 
-E_dihed  =      5239.6299 E_impro  =       227.1218 E_vdwl   =     -1993.2754 
-E_coul   =    206797.6331 E_long   =   -270410.3930 Press    =       237.6701 
-Volume   =    308031.5639 
----------------- Step      100 ----- CPU =     35.3771 (sec) ----------------
-TotEng   =    -25290.7593 KinEng   =     21592.0117 Temp     =       301.0920 
-PotEng   =    -46882.7709 E_bond   =      2567.9807 E_angle  =     10781.9408 
-E_dihed  =      5198.7432 E_impro  =       216.7834 E_vdwl   =     -1902.4783 
-E_coul   =    206659.2326 E_long   =   -270404.9733 Press    =         6.9960 
-Volume   =    308133.9888 
-Loop time of 35.3771 on 1 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 25.4765 (72.0139)
-Bond  time (%) = 1.27905 (3.61547)
-Kspce time (%) = 3.22381 (9.11269)
-Neigh time (%) = 4.26655 (12.0602)
-Comm  time (%) = 0.0692198 (0.195663)
-Outpt time (%) = 0.000253916 (0.00071774)
-Other time (%) = 1.06179 (3.00134)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Nghost:    47958 ave 47958 max 47958 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-Neighs:    1.20281e+07 ave 1.20281e+07 max 1.20281e+07 min
-Histogram: 1 0 0 0 0 0 0 0 0 0
-
-Total # of neighbors = 12028107
-Ave neighs/atom = 375.878
-Ave special neighs/atom = 7.43187
-Neighbor list builds = 11
-Dangerous builds = 0

bench/log.15May15.rhodo.fixed.icc.4

@@ -1,110 +0,0 @@
-LAMMPS (30 Apr 2015)
-# Rhodopsin model
-
-units           real
-neigh_modify    delay 5 every 1
-
-atom_style      full
-bond_style      harmonic
-angle_style     charmm
-dihedral_style  charmm
-improper_style  harmonic
-pair_style      lj/charmm/coul/long 8.0 10.0
-pair_modify     mix arithmetic
-kspace_style    pppm 1e-4
-
-read_data       data.rhodo
-  orthogonal box = (-27.5 -38.5 -36.3646) to (27.5 38.5 36.3615)
-  1 by 2 by 2 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-  scanning bonds ...
-  4 = max bonds/atom
-  scanning angles ...
-  8 = max angles/atom
-  scanning dihedrals ...
-  18 = max dihedrals/atom
-  scanning impropers ...
-  2 = max impropers/atom
-  reading bonds ...
-  27723 bonds
-  reading angles ...
-  40467 angles
-  reading dihedrals ...
-  56829 dihedrals
-  reading impropers ...
-  1034 impropers
-  4 = max # of 1-2 neighbors
-  12 = max # of 1-3 neighbors
-  24 = max # of 1-4 neighbors
-  26 = max # of special neighbors
-
-fix             1 all shake 0.0001 5 0 m 1.0 a 232
-  1617 = # of size 2 clusters
-  3633 = # of size 3 clusters
-  747 = # of size 4 clusters
-  4233 = # of frozen angles
-fix             2 all npt temp 300.0 300.0 100.0 		z 0.0 0.0 1000.0 mtk no pchain 0 tchain 1
-
-special_bonds   charmm
-
-thermo          50
-thermo_style    multi
-timestep        2.0
-
-run		100
-PPPM initialization ...
-  G vector (1/distance) = 0.248835
-  grid = 25 32 32
-  stencil order = 5
-  estimated absolute RMS force accuracy = 0.0355478
-  estimated relative force accuracy = 0.000107051
-  using double precision FFTs
-  3d grid and FFT values/proc = 13230 6400
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 5 steps, check yes
-  master list distance cutoff = 12
-Memory usage per processor = 36.629 Mbytes
----------------- Step        0 ----- CPU =      0.0000 (sec) ----------------
-TotEng   =    -25356.2064 KinEng   =     21444.8313 Temp     =       299.0397 
-PotEng   =    -46801.0377 E_bond   =      2537.9940 E_angle  =     10921.3742 
-E_dihed  =      5211.7865 E_impro  =       213.5116 E_vdwl   =     -2307.8634 
-E_coul   =    207025.8927 E_long   =   -270403.7333 Press    =      -142.6035 
-Volume   =    307995.0335 
----------------- Step       50 ----- CPU =      4.6438 (sec) ----------------
-TotEng   =    -25330.0828 KinEng   =     21501.0029 Temp     =       299.8230 
-PotEng   =    -46831.0857 E_bond   =      2471.7004 E_angle  =     10836.4975 
-E_dihed  =      5239.6299 E_impro  =       227.1218 E_vdwl   =     -1993.2754 
-E_coul   =    206797.6331 E_long   =   -270410.3930 Press    =       237.6701 
-Volume   =    308031.5639 
----------------- Step      100 ----- CPU =      9.4301 (sec) ----------------
-TotEng   =    -25290.7591 KinEng   =     21592.0117 Temp     =       301.0920 
-PotEng   =    -46882.7708 E_bond   =      2567.9807 E_angle  =     10781.9408 
-E_dihed  =      5198.7432 E_impro  =       216.7834 E_vdwl   =     -1902.4783 
-E_coul   =    206659.2327 E_long   =   -270404.9733 Press    =         6.9960 
-Volume   =    308133.9888 
-Loop time of 9.43015 on 4 procs for 100 steps with 32000 atoms
-
-Pair  time (%) = 6.53815 (69.3324)
-Bond  time (%) = 0.323679 (3.43239)
-Kspce time (%) = 1.02664 (10.8868)
-Neigh time (%) = 1.11839 (11.8597)
-Comm  time (%) = 0.0812459 (0.861554)
-Outpt time (%) = 0.000150442 (0.00159533)
-Other time (%) = 0.341896 (3.62557)
-
-Nlocal:    8000 ave 8143 max 7933 min
-Histogram: 1 2 0 0 0 0 0 0 0 1
-Nghost:    22733.5 ave 22769 max 22693 min
-Histogram: 1 0 0 0 0 2 0 0 0 1
-Neighs:    3.00703e+06 ave 3.0975e+06 max 2.96493e+06 min
-Histogram: 1 2 0 0 0 0 0 0 0 1
-
-Total # of neighbors = 12028107
-Ave neighs/atom = 375.878
-Ave special neighs/atom = 7.43187
-Neighbor list builds = 11
-Dangerous builds = 0

bench/log.15May15.rhodo.scaled.icc.4

@@ -1,131 +0,0 @@
-LAMMPS (30 Apr 2015)
-# Rhodopsin model
-
-variable	x index 1
-variable	y index 1
-variable	z index 1
-
-units           real
-neigh_modify    delay 5 every 1
-
-atom_style      full
-atom_modify	map hash
-bond_style      harmonic
-angle_style     charmm
-dihedral_style  charmm
-improper_style  harmonic
-pair_style      lj/charmm/coul/long 8.0 10.0
-pair_modify     mix arithmetic
-kspace_style    pppm 1e-4
-
-read_data       data.rhodo
-  orthogonal box = (-27.5 -38.5 -36.3646) to (27.5 38.5 36.3615)
-  1 by 2 by 2 MPI processor grid
-  reading atoms ...
-  32000 atoms
-  reading velocities ...
-  32000 velocities
-  scanning bonds ...
-  4 = max bonds/atom
-  scanning angles ...
-  8 = max angles/atom
-  scanning dihedrals ...
-  18 = max dihedrals/atom
-  scanning impropers ...
-  2 = max impropers/atom
-  reading bonds ...
-  27723 bonds
-  reading angles ...
-  40467 angles
-  reading dihedrals ...
-  56829 dihedrals
-  reading impropers ...
-  1034 impropers
-  4 = max # of 1-2 neighbors
-  12 = max # of 1-3 neighbors
-  24 = max # of 1-4 neighbors
-  26 = max # of special neighbors
-
-replicate	$x $y $z
-replicate	2 $y $z
-replicate	2 2 $z
-replicate	2 2 1
-  orthogonal box = (-27.5 -38.5 -36.3646) to (82.5 115.5 36.3615)
-  2 by 2 by 1 MPI processor grid
-  128000 atoms
-  110892 bonds
-  161868 angles
-  227316 dihedrals
-  4136 impropers
-  4 = max # of 1-2 neighbors
-  12 = max # of 1-3 neighbors
-  24 = max # of 1-4 neighbors
-  26 = max # of special neighbors
-
-fix             1 all shake 0.0001 5 0 m 1.0 a 232
-  6468 = # of size 2 clusters
-  14532 = # of size 3 clusters
-  2988 = # of size 4 clusters
-  16932 = # of frozen angles
-fix             2 all npt temp 300.0 300.0 100.0 		z 0.0 0.0 1000.0 mtk no pchain 0 tchain 1
-
-special_bonds   charmm
-
-thermo          50
-thermo_style    multi
-timestep        2.0
-
-run		100
-PPPM initialization ...
-  G vector (1/distance) = 0.248593
-  grid = 48 60 36
-  stencil order = 5
-  estimated absolute RMS force accuracy = 0.0359793
-  estimated relative force accuracy = 0.00010835
-  using double precision FFTs
-  3d grid and FFT values/proc = 41615 25920
-Neighbor list info ...
-  1 neighbor list requests
-  update every 1 steps, delay 5 steps, check yes
-  master list distance cutoff = 12
-Memory usage per processor = 95.5339 Mbytes
----------------- Step        0 ----- CPU =      0.0000 (sec) ----------------
-TotEng   =   -101425.4887 KinEng   =     85779.3251 Temp     =       299.0304 
-PotEng   =   -187204.8138 E_bond   =     10151.9760 E_angle  =     43685.4968 
-E_dihed  =     20847.1460 E_impro  =       854.0463 E_vdwl   =     -9231.4537 
-E_coul   =    827053.5824 E_long   =  -1080565.6077 Press    =      -142.3092 
-Volume   =   1231980.1340 
----------------- Step       50 ----- CPU =     18.5923 (sec) ----------------
-TotEng   =   -101320.2677 KinEng   =     86003.4837 Temp     =       299.8118 
-PotEng   =   -187323.7514 E_bond   =      9887.1072 E_angle  =     43346.7922 
-E_dihed  =     20958.7032 E_impro  =       908.4715 E_vdwl   =     -7973.4457 
-E_coul   =    826141.3831 E_long   =  -1080592.7629 Press    =       238.0161 
-Volume   =   1232126.1855 
----------------- Step      100 ----- CPU =     38.1551 (sec) ----------------
-TotEng   =   -101158.1849 KinEng   =     86355.6149 Temp     =       301.0393 
-PotEng   =   -187513.7998 E_bond   =     10272.0693 E_angle  =     43128.6454 
-E_dihed  =     20793.9759 E_impro  =       867.0826 E_vdwl   =     -7586.7186 
-E_coul   =    825583.7122 E_long   =  -1080572.5667 Press    =        15.2151 
-Volume   =   1232535.8423 
-Loop time of 38.1551 on 4 procs for 100 steps with 128000 atoms
-
-Pair  time (%) = 26.4472 (69.3149)
-Bond  time (%) = 1.31402 (3.44388)
-Kspce time (%) = 4.23553 (11.1008)
-Neigh time (%) = 4.45503 (11.6761)
-Comm  time (%) = 0.208946 (0.547622)
-Outpt time (%) = 0.000290096 (0.000760307)
-Other time (%) = 1.49411 (3.91587)
-
-Nlocal:    32000 ave 32000 max 32000 min
-Histogram: 4 0 0 0 0 0 0 0 0 0
-Nghost:    47957 ave 47957 max 47957 min
-Histogram: 4 0 0 0 0 0 0 0 0 0
-Neighs:    1.20281e+07 ave 1.20572e+07 max 1.1999e+07 min
-Histogram: 2 0 0 0 0 0 0 0 0 2
-
-Total # of neighbors = 48112472
-Ave neighs/atom = 375.879
-Ave special neighs/atom = 7.43187
-Neighbor list builds = 11
-Dangerous builds = 0

doc/.gitignore

@@ -0,0 +1 @@
+

doc/Eqs/cna_cutoff1.tex

@@ -1,14 +0,0 @@
-\documentclass[12pt,article]{article}
-
-\usepackage{indentfirst}
-\usepackage{amsmath}
-
-\begin{document}
-
-\begin{eqnarray*}
-  r_{c}^{fcc} & = & \frac{1}{2} \left(\frac{\sqrt{2}}{2} + 1\right) \mathrm{a} \simeq 0.8536 \:\mathrm{a} \\
-  r_{c}^{bcc} & = & \frac{1}{2}(\sqrt{2} + 1) \mathrm{a} \simeq 1.207 \:\mathrm{a} \\
-  r_{c}^{hcp} & = & \frac{1}{2}\left(1+\sqrt{\frac{4+2x^{2}}{3}}\right) \mathrm{a}
-\end{eqnarray*}
-
-\end{document}

doc/Eqs/cna_cutoff2.tex

@@ -1,12 +0,0 @@
-\documentclass[12pt,article]{article}
-
-\usepackage{indentfirst}
-\usepackage{amsmath}
-
-\begin{document}
-
-$$
-  Rc + Rs > 2*{\rm cutoff}
-$$
-
-\end{document}

doc/Eqs/eff_ECP1.tex

@@ -1,9 +0,0 @@
-\documentstyle[12pt]{article}
-
-\begin{document}
-
-$$
-E_{Pauli(ECP_s)}=p_1\exp\left(-\frac{p_2r^2}{p_3+s^2} \right)
-$$
-
-\end{document}  

doc/Eqs/eff_ECP2.tex

@@ -1,8 +0,0 @@
-\documentstyle[12pt]{article}
-
-\begin{document}
-
-$$
-E_{Pauli(ECP_p)}=p_1\left( \frac{2}{p_2/s+s/p_2} \right)\left( r-p_3s\right)^2\exp \left[ -\frac{p_4\left( r-p_3s \right)^2}{p_5+s^2} \right] 
-$$
-

doc/Eqs/fix_nh1.tex

@@ -1,35 +0,0 @@
-\documentclass[24pt]{article}
-
-\pagestyle{empty}
-\Huge
-
-\begin{document}
-
-\mathchardef\mhyphen="2D
-
-% The imaginary unit
-\providecommand*{\iu}%
-	{\ensuremath{{\rm i}}}
-
-
-\begin{eqnarray*}
-\exp \left(\iu{} L \Delta t \right) &=&<EFBFBD>
-\exp \left(\iu{} L_{\rm T\mhyphen baro} \frac{\Delta t}{2} \right)
-\exp \left(\iu{} L_{\rm T\mhyphen part} \frac{\Delta t}{2} \right)
-\exp \left(\iu{} L_{\epsilon , 2} \frac{\Delta t}{2} \right)
-\exp \left(\iu{} L_{2}^{(2)} \frac{\Delta t}{2} \right) \\
-&&\times \left[ 
-\exp \left(\iu{} L_{2}^{(1)} \frac{\Delta t}{2n} \right)
-\exp \left(\iu{} L_{\epsilon , 1} \frac{\Delta t}{n} \right)
-\exp \left(\iu{} L_1 \frac{\Delta t}{n} \right)
-\exp \left(\iu{} L_{2}^{(1)} \frac{\Delta t}{2n} \right)
-\right]^n \\
-&&\times
-\exp \left(\iu{} L_{2}^{(2)} \frac{\Delta t}{2} \right)
-\exp \left(\iu{} L_{\epsilon , 2} \frac{\Delta t}{2} \right) 
-\exp \left(\iu{} L_{\rm T\mhyphen part} \frac{\Delta t}{2} \right) 
-\exp \left(\iu{} L_{\rm T\mhyphen baro} \frac{\Delta t}{2} \right) \\
-&&+ \mathcal{O} \left(\Delta t^3 \right)
-\end{eqnarray*}
-
-\end{document}

doc/Eqs/fix_ti_rs_force.tex

@@ -1,11 +0,0 @@
-\documentclass[12pt]{article}
-
-\usepackage{amsmath}
-
-\begin{document}
-
-$$
-  F_{\text{total}} = \lambda F_{\text{int}}
-$$
-
-\end{document}

doc/Eqs/fix_ti_rs_function_1.tex

@@ -1,9 +0,0 @@
-\documentclass[12pt]{article}
-
-\begin{document}
-
-$$
-  \lambda(\tau) = \lambda_i + \tau \left( \lambda_f - \lambda_i \right)
-$$
-
-\end{document}

doc/Eqs/fix_ti_rs_function_2.tex

@@ -1,9 +0,0 @@
-\documentclass[12pt]{article}
-
-\begin{document}
-
-$$
-  \lambda(\tau) = \frac{\lambda_i}{1 + \tau \left( \frac{\lambda_i}{\lambda_f} - 1 \right)}
-$$
-
-\end{document}

doc/Eqs/fix_ti_rs_function_3.tex

@@ -1,9 +0,0 @@
-\documentclass[12pt]{article}
-
-\begin{document}
-
-$$
-  \lambda(\tau) = \frac{\lambda_i}{ 1 + \log_2(1+\tau) \left( \frac{\lambda_i}{\lambda_f} - 1 \right)}
-$$
-
-\end{document}

doc/Eqs/fix_ti_spring_force.tex

@@ -1,11 +0,0 @@
-\documentclass[12pt]{article}
-
-\usepackage{amsmath}
-
-\begin{document}
-
-$$
-  F_{\text{total}} = \left( 1-\lambda \right) F_{\text{solid}} + \lambda F_{\text{harm}}
-$$
-
-\end{document}

doc/Eqs/fix_wall_lj1043.tex

@@ -1,12 +0,0 @@
-\documentstyle[12pt]{article}
-
-\begin{document}
-
-$$
- E = 2 \pi \epsilon \left[ \frac{2}{5} \left(\frac{\sigma}{r}\right)^{10} - 
-                       \left(\frac{\sigma}{r}\right)^4 -
-                       \frac{\sqrt(2)\sigma^3}{3\left(r+\left(0.61/\sqrt(2)\right)\sigma\right)^3}\right]
-                       \qquad r < r_c
-$$
-
-\end{document}

doc/Eqs/heat_flux_k.tex

@@ -1,11 +0,0 @@
-\documentclass[12pt]{article}
-
-\begin{document}
-
-$$
-\kappa  = \frac{V}{k_B T^2} \int_0^\infty \langle J_x(0)  J_x(t) \rangle \, dt
-= \frac{V}{3 k_B T^2} \int_0^\infty \langle \mathbf{J}(0) \cdot  \mathbf{J}(t)  \rangle \, dt
-$$
-
-\end{document}
-

doc/Eqs/improper_umbrella.tex

@@ -1,13 +0,0 @@
-\documentstyle[12pt]{article}
-
-\begin{document}
-
-$$
-E=\frac{1}{2}K\left( \frac{1+cos\omega_0}{sin\omega_0}\right) ^2 \left( cos\omega - cos\omega_0\right) \qquad \omega_0 \neq 0^o
-$$
-
-$$
-E=K\left( 1-cos\omega\right)  \qquad \omega_0 = 0^o
-$$
-
-\end{document}

doc/Eqs/pair_comb1.tex

@@ -1,7 +0,0 @@
-\documentclass[12pt]{article}
-\begin{document} \large
-\begin{eqnarray*}
-E_T & = & \sum_i [ E_i^{self} (q_i) + \sum_{j>i} [E_{ij}^{short} (r_{ij}, q_i, q_j) + E_{ij}^{Coul} (r_{ij}, q_i, q_j)] + \\
-&& E^{polar} (q_i, r_{ij}) + E^{vdW} (r_{ij}) + E^{barr} (q_i) + E^{corr} (r_{ij}, \theta_{jik})] \\
-\end{eqnarray*}                           
-\end{document}

doc/Eqs/pair_comb2.tex

@@ -1,23 +0,0 @@
-\documentclass[10pt]{article}
-
-\begin{document}
-
-\begin{table}[h]
-\begin{tabular}{|c|c|c|c|c|c|c|c|c|}
-\hline
-   & $O$ & $Cu$ & $N$ & $C$ & $H$ & $Ti$ & $Zn$ & $Zr$ \\ \hline
-$O$	& F & F & F & F & F & F & F & F\\ \hline
-$Cu$	& F & F & P & F & F & P & F & P \\ \hline
-$N$ 	& F & P & F & M & F & P & P & P \\ \hline
-$C$   	& F & F & M & F & F & M & M & M \\ \hline
-$H$   	& F & F & F & F & F & M & M & F \\ \hline
-$Ti$   	& F & P & P & M & M & F & P & P \\ \hline
-$Zn$  	& F & F & P & M & M & P & F & P \\ \hline
-$Zr$  	& F & P & P & M & F & P & P & F \\ \hline
-\multicolumn{9}{l}{F: Fully optimized} \\
-\multicolumn{9}{l}{M: Only optimized for dimer molecule} \\
-\multicolumn{9}{l}{P: in Progress but have it from mixing rule} \\
-\end{tabular}
-\end{table}
-
-\end{document}

doc/Makefile

@@ -0,0 +1,87 @@
+# Makefile for LAMMPS documentation
+SHA1          = $(shell echo $USER-$PWD | python utils/sha1sum.py)
+BUILDDIR      = /tmp/lammps-docs-$(SHA1)
+RSTDIR        = $(BUILDDIR)/rst
+VENV          = $(BUILDDIR)/docenv
+TXT2RST       = $(VENV)/bin/txt2rst
+
+PYTHON        = $(shell which python3)
+
+ifeq ($(shell which python3 >/dev/null 2>&1; echo $$?), 1)
+$(error Python3 was not found! Please check README.md for further instructions)
+endif
+
+ifeq ($(shell which virtualenv >/dev/null 2>&1; echo $$?), 1)
+$(error virtualenv was not found! Please check README.md for further instructions)
+endif
+
+SOURCES=$(wildcard src/*.txt)
+OBJECTS=$(SOURCES:src/%.txt=$(RSTDIR)/%.rst)
+
+.PHONY: help clean-all clean html pdf venv
+
+help:
+	@echo "Please use \`make <target>' where <target> is one of"
+	@echo "  html       to make HTML version of documentation using Sphinx"
+	@echo "  pdf        to make Manual.pdf"
+	@echo "  txt2html   to build txt2html tool"
+	@echo "  clean      to remove all generated RST files"
+	@echo "  clean-all  to reset the entire build environment"
+
+clean-all:
+	rm -rf $(BUILDDIR)/* utils/txt2html/txt2html.exe
+
+clean:
+	rm -rf $(RSTDIR)
+
+txt2html: utils/txt2html/txt2html.exe
+
+html: $(OBJECTS)
+	@(\
+		. $(VENV)/bin/activate ;\
+		cp -r src/* $(RSTDIR)/ ;\
+		sphinx-build -j 8 -b html -c utils/sphinx-config -d $(BUILDDIR)/doctrees $(RSTDIR) html ;\
+		deactivate ;\
+	)
+	-rm html/searchindex.js
+	-rm -rf html/_sources
+	@echo "Build finished. The HTML pages are in doc/html."
+
+pdf: utils/txt2html/txt2html.exe
+	@(\
+		cd src; \
+		../utils/txt2html/txt2html.exe -b *.txt; \
+		htmldoc --batch ../lammps.book;          \
+		for s in `echo *.txt | sed -e 's,\.txt,\.html,g'` ; \
+			do grep -q $$s ../lammps.book || \
+			echo doc file $$s missing in lammps.book; done; \
+		rm *.html; \
+	)
+
+utils/txt2html/txt2html.exe: utils/txt2html/txt2html.cpp
+	g++ -O -Wall -o $@ $<
+
+$(RSTDIR)/%.rst : src/%.txt $(TXT2RST)
+	@(\
+		mkdir -p $(RSTDIR) ; \
+		. $(VENV)/bin/activate ;\
+		txt2rst $< > $@ ;\
+		deactivate ;\
+	)
+
+$(VENV):
+	@( \
+		virtualenv -p $(PYTHON) $(VENV); \
+		. $(VENV)/bin/activate; \
+		pip install Sphinx; \
+		pip install sphinxcontrib-images; \
+		deactivate;\
+	)
+
+$(TXT2RST): $(VENV)
+	@( \
+		. $(VENV)/bin/activate; \
+		(cd utils/converters;\
+		python setup.py develop);\
+		deactivate;\
+	)

doc/Manual.html

@@ -1,456 +0,0 @@
-
-
-<!DOCTYPE html>
-<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
-<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]-->
-<head>
-  <meta charset="utf-8">
-  
-  <meta name="viewport" content="width=device-width, initial-scale=1.0">
-  
-  <title>LAMMPS Documentation &mdash; LAMMPS 15 May 2015 version documentation</title>
-  
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-  
-  
-
-  
-
-  
-  
-    
-
-  
-
-  
-  
-    <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
-  
-
-  
-    <link rel="stylesheet" href="_static/sphinxcontrib-images/LightBox2/lightbox2/css/lightbox.css" type="text/css" />
-  
-
-  
-    <link rel="top" title="LAMMPS 15 May 2015 version documentation" href="index.html"/>
-        <link rel="next" title="1. Introduction" href="Section_intro.html"/> 
-
-  
-  <script src="_static/js/modernizr.min.js"></script>
-
-</head>
-
-<body class="wy-body-for-nav" role="document">
-
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-<div role="search">
-  <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
-    <input type="hidden" name="check_keywords" value="yes" />
-    <input type="hidden" name="area" value="default" />
-  </form>
-</div>
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-<li class="toctree-l1"><a class="reference internal" href="Section_commands.html">3. Commands</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="Section_howto.html">6. How-to discussions</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_example.html">7. Example problems</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_perf.html">8. Performance &amp; scalability</a></li>
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-            
-  <H1></H1><div class="section" id="lammps-documentation">
-<h1>LAMMPS Documentation<a class="headerlink" href="#lammps-documentation" title="Permalink to this headline">¶</a></h1>
-<div class="section" id="dec-2015-version">
-<h2>7 Dec 2015 version<a class="headerlink" href="#dec-2015-version" title="Permalink to this headline">¶</a></h2>
-</div>
-<div class="section" id="version-info">
-<h2>Version info:<a class="headerlink" href="#version-info" title="Permalink to this headline">¶</a></h2>
-<p>The LAMMPS &#8220;version&#8221; is the date when it was released, such as 1 May
-2010. LAMMPS is updated continuously.  Whenever we fix a bug or add a
-feature, we release it immediately, and post a notice on <a class="reference external" href="http://lammps.sandia.gov/bug.html">this page of the WWW site</a>.  Each dated copy of LAMMPS contains all the
-features and bug-fixes up to and including that version date. The
-version date is printed to the screen and logfile every time you run
-LAMMPS. It is also in the file src/version.h and in the LAMMPS
-directory name created when you unpack a tarball, and at the top of
-the first page of the manual (this page).</p>
-<ul class="simple">
-<li>If you browse the HTML doc pages on the LAMMPS WWW site, they always
-describe the most current version of LAMMPS.</li>
-<li>If you browse the HTML doc pages included in your tarball, they
-describe the version you have.</li>
-<li>The <a class="reference external" href="Manual.pdf">PDF file</a> on the WWW site or in the tarball is updated
-about once per month.  This is because it is large, and we don&#8217;t want
-it to be part of every patch.</li>
-<li>There is also a <a class="reference external" href="Developer.pdf">Developer.pdf</a> file in the doc
-directory, which describes the internal structure and algorithms of
-LAMMPS.</li>
-</ul>
-<p>LAMMPS stands for Large-scale Atomic/Molecular Massively Parallel
-Simulator.</p>
-<p>LAMMPS is a classical molecular dynamics simulation code designed to
-run efficiently on parallel computers.  It was developed at Sandia
-National Laboratories, a US Department of Energy facility, with
-funding from the DOE.  It is an open-source code, distributed freely
-under the terms of the GNU Public License (GPL).</p>
-<p>The primary developers of LAMMPS are <a class="reference external" href="http://www.sandia.gov/~sjplimp">Steve Plimpton</a>, Aidan
-Thompson, and Paul Crozier who can be contacted at
-sjplimp,athomps,pscrozi at sandia.gov.  The <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a> at
-<a class="reference external" href="http://lammps.sandia.gov">http://lammps.sandia.gov</a> has more information about the code and its
-uses.</p>
-<hr class="docutils" />
-<p>The LAMMPS documentation is organized into the following sections.  If
-you find errors or omissions in this manual or have suggestions for
-useful information to add, please send an email to the developers so
-we can improve the LAMMPS documentation.</p>
-<p>Once you are familiar with LAMMPS, you may want to bookmark <a class="reference internal" href="Section_commands.html#comm"><span>this page</span></a> at Section_commands.html#comm since
-it gives quick access to documentation for all LAMMPS commands.</p>
-<p><a class="reference external" href="Manual.pdf">PDF file</a> of the entire manual, generated by
-<a class="reference external" href="http://freecode.com/projects/htmldoc">htmldoc</a></p>
-<div class="toctree-wrapper compound">
-<ul>
-<li class="toctree-l1"><a class="reference internal" href="Section_intro.html">1. Introduction</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_intro.html#what-is-lammps">1.1. What is LAMMPS</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_intro.html#lammps-features">1.2. LAMMPS features</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_intro.html#lammps-non-features">1.3. LAMMPS non-features</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_intro.html#open-source-distribution">1.4. Open source distribution</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_intro.html#acknowledgments-and-citations">1.5. Acknowledgments and citations</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_start.html">2. Getting Started</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#what-s-in-the-lammps-distribution">2.1. What&#8217;s in the LAMMPS distribution</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#making-lammps">2.2. Making LAMMPS</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#making-lammps-with-optional-packages">2.3. Making LAMMPS with optional packages</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#building-lammps-via-the-make-py-tool">2.4. Building LAMMPS via the Make.py tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#building-lammps-as-a-library">2.5. Building LAMMPS as a library</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#running-lammps">2.6. Running LAMMPS</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#command-line-options">2.7. Command-line options</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#lammps-screen-output">2.8. LAMMPS screen output</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_start.html#tips-for-users-of-previous-lammps-versions">2.9. Tips for users of previous LAMMPS versions</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_commands.html">3. Commands</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#lammps-input-script">3.1. LAMMPS input script</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#parsing-rules">3.2. Parsing rules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#input-script-structure">3.3. Input script structure</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#commands-listed-by-category">3.4. Commands listed by category</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#individual-commands">3.5. Individual commands</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#fix-styles">3.6. Fix styles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#compute-styles">3.7. Compute styles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#pair-style-potentials">3.8. Pair_style potentials</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#bond-style-potentials">3.9. Bond_style potentials</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#angle-style-potentials">3.10. Angle_style potentials</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#dihedral-style-potentials">3.11. Dihedral_style potentials</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#improper-style-potentials">3.12. Improper_style potentials</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_commands.html#kspace-solvers">3.13. Kspace solvers</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_packages.html">4. Packages</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#standard-packages">4.1. Standard packages</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-compress-package">4.2. Build instructions for COMPRESS package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-gpu-package">4.3. Build instructions for GPU package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-kim-package">4.4. Build instructions for KIM package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-kokkos-package">4.5. Build instructions for KOKKOS package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-kspace-package">4.6. Build instructions for KSPACE package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-meam-package">4.7. Build instructions for MEAM package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-poems-package">4.8. Build instructions for POEMS package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-python-package">4.9. Build instructions for PYTHON package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-reax-package">4.10. Build instructions for REAX package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-voronoi-package">4.11. Build instructions for VORONOI package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#build-instructions-for-xtc-package">4.12. Build instructions for XTC package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-packages">4.13. User packages</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-atc-package">4.14. USER-ATC package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-awpmd-package">4.15. USER-AWPMD package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-cg-cmm-package">4.16. USER-CG-CMM package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-colvars-package">4.17. USER-COLVARS package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-cuda-package">4.18. USER-CUDA package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-diffraction-package">4.19. USER-DIFFRACTION package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-drude-package">4.20. USER-DRUDE package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-eff-package">4.21. USER-EFF package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-fep-package">4.22. USER-FEP package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-h5md-package">4.23. USER-H5MD package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-intel-package">4.24. USER-INTEL package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-lb-package">4.25. USER-LB package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-mgpt-package">4.26. USER-MGPT package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-misc-package">4.27. USER-MISC package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-molfile-package">4.28. USER-MOLFILE package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-omp-package">4.29. USER-OMP package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-phonon-package">4.30. USER-PHONON package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-qmmm-package">4.31. USER-QMMM package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-qtb-package">4.32. USER-QTB package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-reaxc-package">4.33. USER-REAXC package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-smd-package">4.34. USER-SMD package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-smtbq-package">4.35. USER-SMTBQ package</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_packages.html#user-sph-package">4.36. USER-SPH package</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_accelerate.html">5. Accelerating LAMMPS performance</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_accelerate.html#measuring-performance">5.1. Measuring performance</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_accelerate.html#general-strategies">5.2. General strategies</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_accelerate.html#packages-with-optimized-styles">5.3. Packages with optimized styles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_accelerate.html#comparison-of-various-accelerator-packages">5.4. Comparison of various accelerator packages</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_howto.html">6. How-to discussions</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#restarting-a-simulation">6.1. Restarting a simulation</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#d-simulations">6.2. 2d simulations</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#charmm-amber-and-dreiding-force-fields">6.3. CHARMM, AMBER, and DREIDING force fields</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#running-multiple-simulations-from-one-input-script">6.4. Running multiple simulations from one input script</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#multi-replica-simulations">6.5. Multi-replica simulations</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#granular-models">6.6. Granular models</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#tip3p-water-model">6.7. TIP3P water model</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#tip4p-water-model">6.8. TIP4P water model</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#spc-water-model">6.9. SPC water model</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#coupling-lammps-to-other-codes">6.10. Coupling LAMMPS to other codes</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#visualizing-lammps-snapshots">6.11. Visualizing LAMMPS snapshots</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#triclinic-non-orthogonal-simulation-boxes">6.12. Triclinic (non-orthogonal) simulation boxes</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#nemd-simulations">6.13. NEMD simulations</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#finite-size-spherical-and-aspherical-particles">6.14. Finite-size spherical and aspherical particles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#output-from-lammps-thermo-dumps-computes-fixes-variables">6.15. Output from LAMMPS (thermo, dumps, computes, fixes, variables)</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#thermostatting-barostatting-and-computing-temperature">6.16. Thermostatting, barostatting, and computing temperature</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#walls">6.17. Walls</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#elastic-constants">6.18. Elastic constants</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#library-interface-to-lammps">6.19. Library interface to LAMMPS</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#calculating-thermal-conductivity">6.20. Calculating thermal conductivity</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#calculating-viscosity">6.21. Calculating viscosity</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#calculating-a-diffusion-coefficient">6.22. Calculating a diffusion coefficient</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#using-chunks-to-calculate-system-properties">6.23. Using chunks to calculate system properties</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#setting-parameters-for-the-kspace-style-pppm-disp-command">6.24. Setting parameters for the <code class="docutils literal"><span class="pre">kspace_style</span> <span class="pre">pppm/disp</span></code> command</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#polarizable-models">6.25. Polarizable models</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#adiabatic-core-shell-model">6.26. Adiabatic core/shell model</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_howto.html#drude-induced-dipoles">6.27. Drude induced dipoles</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_example.html">7. Example problems</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_perf.html">8. Performance &amp; scalability</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_tools.html">9. Additional tools</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#amber2lmp-tool">9.1. amber2lmp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#binary2txt-tool">9.2. binary2txt tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#ch2lmp-tool">9.3. ch2lmp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#chain-tool">9.4. chain tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#colvars-tools">9.5. colvars tools</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#createatoms-tool">9.6. createatoms tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#data2xmovie-tool">9.7. data2xmovie tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#eam-database-tool">9.8. eam database tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#eam-generate-tool">9.9. eam generate tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#eff-tool">9.10. eff tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#emacs-tool">9.11. emacs tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#fep-tool">9.12. fep tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#i-pi-tool">9.13. i-pi tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#ipp-tool">9.14. ipp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#kate-tool">9.15. kate tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#lmp2arc-tool">9.16. lmp2arc tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#lmp2cfg-tool">9.17. lmp2cfg tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#lmp2vmd-tool">9.18. lmp2vmd tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#matlab-tool">9.19. matlab tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#micelle2d-tool">9.20. micelle2d tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#moltemplate-tool">9.21. moltemplate tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#msi2lmp-tool">9.22. msi2lmp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#phonon-tool">9.23. phonon tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#polymer-bonding-tool">9.24. polymer bonding tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#pymol-asphere-tool">9.25. pymol_asphere tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#python-tool">9.26. python tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#reax-tool">9.27. reax tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#restart2data-tool">9.28. restart2data tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#vim-tool">9.29. vim tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#xmgrace-tool">9.30. xmgrace tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_tools.html#xmovie-tool">9.31. xmovie tool</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_modify.html">10. Modifying &amp; extending LAMMPS</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#atom-styles">10.1. Atom styles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#bond-angle-dihedral-improper-potentials">10.2. Bond, angle, dihedral, improper potentials</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#compute-styles">10.3. Compute styles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#dump-styles">10.4. Dump styles</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#dump-custom-output-options">10.5. Dump custom output options</a></li>
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-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#input-script-commands">10.7. Input script commands</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#kspace-computations">10.8. Kspace computations</a></li>
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-<li class="toctree-l2"><a class="reference internal" href="Section_modify.html#submitting-new-features-for-inclusion-in-lammps">10.15. Submitting new features for inclusion in LAMMPS</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_python.html">11. Python interface to LAMMPS</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#overview-of-running-lammps-from-python">11.1. Overview of running LAMMPS from Python</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#overview-of-using-python-from-a-lammps-script">11.2. Overview of using Python from a LAMMPS script</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#building-lammps-as-a-shared-library">11.3. Building LAMMPS as a shared library</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#installing-the-python-wrapper-into-python">11.4. Installing the Python wrapper into Python</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#extending-python-with-mpi-to-run-in-parallel">11.5. Extending Python with MPI to run in parallel</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#testing-the-python-lammps-interface">11.6. Testing the Python-LAMMPS interface</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#using-lammps-from-python">11.7. Using LAMMPS from Python</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_python.html#example-python-scripts-that-use-lammps">11.8. Example Python scripts that use LAMMPS</a></li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="Section_errors.html">12. Errors</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="Section_errors.html#common-problems">12.1. Common problems</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_errors.html#reporting-bugs">12.2. Reporting bugs</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_errors.html#error-warning-messages">12.3. Error &amp; warning messages</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_errors.html#error">12.4. Errors:</a></li>
-<li class="toctree-l2"><a class="reference internal" href="Section_errors.html#warnings">12.5. Warnings:</a></li>
-</ul>
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-<li class="toctree-l2"><a class="reference internal" href="Section_history.html#coming-attractions">13.1. Coming attractions</a></li>
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-<div class="section" id="indices-and-tables">
-<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this headline">¶</a></h1>
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doc/README.md

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+# Generation of LAMMPS Documentation
+
+The generation of all the documentation is managed by the Makefile inside the
+`doc/` folder.
+
+## Usage:
+
+```bash
+make html         # generate HTML using Sphinx
+make pdf          # generate PDF using htmldoc
+make clean        # remove generated RST files
+make clean-all    # remove entire build folder and any cached data
+```
+
+## Installing prerequisites
+
+To run the documention build toolchain, Python 3 and virtualenv have
+to be installed. Here are instructions for common setups:
+
+### Ubuntu
+
+```bash
+sudo apt-get install python-virtualenv
+```
+
+### Fedora (up to version 21), Red Hat Enterprise Linux or CentOS (up to version 7.x)
+
+```bash
+sudo yum install python3-virtualenv
+```
+
+### Fedora (since version 22)
+
+```bash
+sudo dnf install python3-virtualenv
+```
+
+### MacOS X
+
+## Python 3
+
+Download the latest Python 3 MacOS X package from https://www.python.org and install it.
+This will install both Python 3 and pip3.
+
+## virtualenv
+
+Once Python 3 is installed, open a Terminal and type `pip3 install virtualenv`. This will
+install virtualenv from the Python Package Index.

doc/Scripts/correlate.py

@@ -1,89 +0,0 @@
-#!/usr/bin/env python
-"""
-  function: 
-    parse the block of thermo data in a lammps logfile and perform auto- and 
-    cross correlation of the specified column data.  The total sum of the 
-    correlation is also computed which can be converted to an integral by 
-    multiplying by the timestep. 
-  output:
-    standard output contains column data for the auto- & cross correlations 
-    plus the total sum of each. Note, only the upper triangle of the 
-    correlation matrix is computed.
-  usage: 
-    correlate.py [-c col] <-c col2> <-s max_correlation_time>  [logfile] 
-"""
-import sys
-import re
-import array
-
-# parse command line
-
-maxCorrelationTime = 0
-cols = array.array("I")
-nCols = 0
-args = sys.argv[1:]
-index = 0
-while index < len(args):
-  arg = args[index]
-  index += 1
-  if   (arg == "-c"):
-    cols.append(int(args[index])-1)
-    nCols += 1
-    index += 1
-  elif (arg == "-s"):
-    maxCorrelationTime = int(args[index])
-    index += 1
-  else :
-    filename = arg
-if (nCols < 1): raise RuntimeError, 'no data columns requested'
-data = [array.array("d")]
-for s in range(1,nCols)  : data.append( array.array("d") )
-
-# read data block from log file
-
-start = False
-input = open(filename)
-nSamples = 0
-pattern = re.compile('\d')
-line = input.readline()
-while line :
-  columns = line.split()
-  if (columns and pattern.match(columns[0])) :
-    for i in range(nCols): 
-      data[i].append( float(columns[cols[i]]) )
-    nSamples += 1
-    start = True
-  else :
-     if (start) : break
-  line = input.readline()
-print "# read :",nSamples," samples of ", nCols," data"
-if( maxCorrelationTime < 1): maxCorrelationTime = int(nSamples/2);
- 
-# correlate and integrate
-
-correlationPairs = []
-for i in range(0,nCols):
-  for j in range(i,nCols): # note only upper triangle of the correlation matrix
-    correlationPairs.append([i,j])
-header = "# "
-for k in range(len(correlationPairs)):
-  i = str(correlationPairs[k][0]+1)
-  j = str(correlationPairs[k][1]+1)
-  header += " C"+i+j+" sum_C"+i+j
-print header
-nCorrelationPairs = len(correlationPairs)
-sum = [0.0] * nCorrelationPairs
-for s in range(maxCorrelationTime)  :
-  correlation = [0.0] * nCorrelationPairs
-  nt = nSamples-s
-  for t in range(0,nt)  :
-    for p in range(nCorrelationPairs):
-      i = correlationPairs[p][0]
-      j = correlationPairs[p][1]
-      correlation[p] += data[i][t]*data[j][s+t]
-  output = ""
-  for p in range(0,nCorrelationPairs):
-    correlation[p] /= nt
-    sum[p] += correlation[p]
-    output += str(correlation[p]) + " " + str(sum[p]) + " "
-  print output

doc/Section_accelerate.html

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-<li class="toctree-l2"><a class="reference internal" href="#measuring-performance">5.1. Measuring performance</a></li>
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-            
-  <div class="section" id="accelerating-lammps-performance">
-<h1>5. Accelerating LAMMPS performance<a class="headerlink" href="#accelerating-lammps-performance" title="Permalink to this headline">¶</a></h1>
-<p>This section describes various methods for improving LAMMPS
-performance for different classes of problems running on different
-kinds of machines.</p>
-<p>There are two thrusts to the discussion that follows.  The
-first is using code options that implement alternate algorithms
-that can speed-up a simulation.  The second is to use one
-of the several accelerator packages provided with LAMMPS that
-contain code optimized for certain kinds of hardware, including
-multi-core CPUs, GPUs, and Intel Xeon Phi coprocessors.</p>
-<ul class="simple">
-<li>5.1 <a class="reference internal" href="#acc-1"><span>Measuring performance</span></a></li>
-<li>5.2 <a class="reference internal" href="#acc-2"><span>Algorithms and code options to boost performace</span></a></li>
-<li>5.3 <a class="reference internal" href="#acc-3"><span>Accelerator packages with optimized styles</span></a></li>
-<li>5.3.1 <a class="reference internal" href="accelerate_cuda.html"><em>USER-CUDA package</em></a></li>
-<li>5.3.2 <a class="reference internal" href="accelerate_gpu.html"><em>GPU package</em></a></li>
-<li>5.3.3 <a class="reference internal" href="accelerate_intel.html"><em>USER-INTEL package</em></a></li>
-<li>5.3.4 <a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS package</em></a></li>
-<li>5.3.5 <a class="reference internal" href="accelerate_omp.html"><em>USER-OMP package</em></a></li>
-<li>5.3.6 <a class="reference internal" href="accelerate_opt.html"><em>OPT package</em></a></li>
-<li>5.4 <a class="reference internal" href="#acc-4"><span>Comparison of various accelerator packages</span></a></li>
-</ul>
-<p>The <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the LAMMPS
-web site gives performance results for the various accelerator
-packages discussed in Section 5.2, for several of the standard LAMMPS
-benchmark problems, as a function of problem size and number of
-compute nodes, on different hardware platforms.</p>
-<div class="section" id="measuring-performance">
-<span id="acc-1"></span><h2>5.1. Measuring performance<a class="headerlink" href="#measuring-performance" title="Permalink to this headline">¶</a></h2>
-<p>Before trying to make your simulation run faster, you should
-understand how it currently performs and where the bottlenecks are.</p>
-<p>The best way to do this is run the your system (actual number of
-atoms) for a modest number of timesteps (say 100 steps) on several
-different processor counts, including a single processor if possible.
-Do this for an equilibrium version of your system, so that the
-100-step timings are representative of a much longer run.  There is
-typically no need to run for 1000s of timesteps to get accurate
-timings; you can simply extrapolate from short runs.</p>
-<p>For the set of runs, look at the timing data printed to the screen and
-log file at the end of each LAMMPS run.  <a class="reference internal" href="Section_start.html#start-8"><span>This section</span></a> of the manual has an overview.</p>
-<p>Running on one (or a few processors) should give a good estimate of
-the serial performance and what portions of the timestep are taking
-the most time.  Running the same problem on a few different processor
-counts should give an estimate of parallel scalability.  I.e. if the
-simulation runs 16x faster on 16 processors, its 100% parallel
-efficient; if it runs 8x faster on 16 processors, it&#8217;s 50% efficient.</p>
-<p>The most important data to look at in the timing info is the timing
-breakdown and relative percentages.  For example, trying different
-options for speeding up the long-range solvers will have little impact
-if they only consume 10% of the run time.  If the pairwise time is
-dominating, you may want to look at GPU or OMP versions of the pair
-style, as discussed below.  Comparing how the percentages change as
-you increase the processor count gives you a sense of how different
-operations within the timestep are scaling.  Note that if you are
-running with a Kspace solver, there is additional output on the
-breakdown of the Kspace time.  For PPPM, this includes the fraction
-spent on FFTs, which can be communication intensive.</p>
-<p>Another important detail in the timing info are the histograms of
-atoms counts and neighbor counts.  If these vary widely across
-processors, you have a load-imbalance issue.  This often results in
-inaccurate relative timing data, because processors have to wait when
-communication occurs for other processors to catch up.  Thus the
-reported times for &#8220;Communication&#8221; or &#8220;Other&#8221; may be higher than they
-really are, due to load-imbalance.  If this is an issue, you can
-uncomment the MPI_Barrier() lines in src/timer.cpp, and recompile
-LAMMPS, to obtain synchronized timings.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="general-strategies">
-<span id="acc-2"></span><h2>5.2. General strategies<a class="headerlink" href="#general-strategies" title="Permalink to this headline">¶</a></h2>
-<div class="admonition note">
-<p class="first admonition-title">Note</p>
-<p class="last">this section 5.2 is still a work in progress</p>
-</div>
-<p>Here is a list of general ideas for improving simulation performance.
-Most of them are only applicable to certain models and certain
-bottlenecks in the current performance, so let the timing data you
-generate be your guide.  It is hard, if not impossible, to predict how
-much difference these options will make, since it is a function of
-problem size, number of processors used, and your machine.  There is
-no substitute for identifying performance bottlenecks, and trying out
-various options.</p>
-<ul class="simple">
-<li>rRESPA</li>
-<li>2-FFT PPPM</li>
-<li>Staggered PPPM</li>
-<li>single vs double PPPM</li>
-<li>partial charge PPPM</li>
-<li>verlet/split run style</li>
-<li>processor command for proc layout and numa layout</li>
-<li>load-balancing: balance and fix balance</li>
-</ul>
-<p>2-FFT PPPM, also called <em>analytic differentiation</em> or <em>ad</em> PPPM, uses
-2 FFTs instead of the 4 FFTs used by the default <em>ik differentiation</em>
-PPPM. However, 2-FFT PPPM also requires a slightly larger mesh size to
-achieve the same accuracy as 4-FFT PPPM. For problems where the FFT
-cost is the performance bottleneck (typically large problems running
-on many processors), 2-FFT PPPM may be faster than 4-FFT PPPM.</p>
-<p>Staggered PPPM performs calculations using two different meshes, one
-shifted slightly with respect to the other.  This can reduce force
-aliasing errors and increase the accuracy of the method, but also
-doubles the amount of work required. For high relative accuracy, using
-staggered PPPM allows one to half the mesh size in each dimension as
-compared to regular PPPM, which can give around a 4x speedup in the
-kspace time. However, for low relative accuracy, using staggered PPPM
-gives little benefit and can be up to 2x slower in the kspace
-time. For example, the rhodopsin benchmark was run on a single
-processor, and results for kspace time vs. relative accuracy for the
-different methods are shown in the figure below.  For this system,
-staggered PPPM (using ik differentiation) becomes useful when using a
-relative accuracy of slightly greater than 1e-5 and above.</p>
-<img alt="_images/rhodo_staggered.jpg" class="align-center" src="_images/rhodo_staggered.jpg" />
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">Using staggered PPPM may not give the same increase in
-accuracy of energy and pressure as it does in forces, so some caution
-must be used if energy and/or pressure are quantities of interest,
-such as when using a barostat.</p>
-</div>
-<hr class="docutils" />
-</div>
-<div class="section" id="packages-with-optimized-styles">
-<span id="acc-3"></span><h2>5.3. Packages with optimized styles<a class="headerlink" href="#packages-with-optimized-styles" title="Permalink to this headline">¶</a></h2>
-<p>Accelerated versions of various <a class="reference internal" href="pair_style.html"><em>pair_style</em></a>,
-<a class="reference internal" href="fix.html"><em>fixes</em></a>, <a class="reference internal" href="compute.html"><em>computes</em></a>, and other commands have
-been added to LAMMPS, which will typically run faster than the
-standard non-accelerated versions.  Some require appropriate hardware
-to be present on your system, e.g. GPUs or Intel Xeon Phi
-coprocessors.</p>
-<p>All of these commands are in packages provided with LAMMPS.  An
-overview of packages is give in <a class="reference internal" href="Section_packages.html"><em>Section packages</em></a>.</p>
-<p>These are the accelerator packages
-currently in LAMMPS, either as standard or user packages:</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="44%" />
-<col width="56%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td><a class="reference internal" href="accelerate_cuda.html"><em>USER-CUDA</em></a></td>
-<td>for NVIDIA GPUs</td>
-</tr>
-<tr class="row-even"><td><a class="reference internal" href="accelerate_gpu.html"><em>GPU</em></a></td>
-<td>for NVIDIA GPUs as well as OpenCL support</td>
-</tr>
-<tr class="row-odd"><td><a class="reference internal" href="accelerate_intel.html"><em>USER-INTEL</em></a></td>
-<td>for Intel CPUs and Intel Xeon Phi</td>
-</tr>
-<tr class="row-even"><td><a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS</em></a></td>
-<td>for GPUs, Intel Xeon Phi, and OpenMP threading</td>
-</tr>
-<tr class="row-odd"><td><a class="reference internal" href="accelerate_omp.html"><em>USER-OMP</em></a></td>
-<td>for OpenMP threading</td>
-</tr>
-<tr class="row-even"><td><a class="reference internal" href="accelerate_opt.html"><em>OPT</em></a></td>
-<td>generic CPU optimizations</td>
-</tr>
-</tbody>
-</table>
-<p>Inverting this list, LAMMPS currently has acceleration support for
-three kinds of hardware, via the listed packages:</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="10%" />
-<col width="90%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td>Many-core CPUs</td>
-<td><a class="reference internal" href="accelerate_intel.html"><em>USER-INTEL</em></a>, <a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS</em></a>, <a class="reference internal" href="accelerate_omp.html"><em>USER-OMP</em></a>, <a class="reference internal" href="accelerate_opt.html"><em>OPT</em></a> packages</td>
-</tr>
-<tr class="row-even"><td>NVIDIA GPUs</td>
-<td><a class="reference internal" href="accelerate_cuda.html"><em>USER-CUDA</em></a>, <a class="reference internal" href="accelerate_gpu.html"><em>GPU</em></a>, <a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS</em></a> packages</td>
-</tr>
-<tr class="row-odd"><td>Intel Phi</td>
-<td><a class="reference internal" href="accelerate_intel.html"><em>USER-INTEL</em></a>, <a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS</em></a> packages</td>
-</tr>
-</tbody>
-</table>
-<p>Which package is fastest for your hardware may depend on the size
-problem you are running and what commands (accelerated and
-non-accelerated) are invoked by your input script.  While these doc
-pages include performance guidelines, there is no substitute for
-trying out the different packages appropriate to your hardware.</p>
-<p>Any accelerated style has the same name as the corresponding standard
-style, except that a suffix is appended.  Otherwise, the syntax for
-the command that uses the style is identical, their functionality is
-the same, and the numerical results it produces should also be the
-same, except for precision and round-off effects.</p>
-<p>For example, all of these styles are accelerated variants of the
-Lennard-Jones <a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut</em></a>:</p>
-<ul class="simple">
-<li><a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut/cuda</em></a></li>
-<li><a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut/gpu</em></a></li>
-<li><a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut/intel</em></a></li>
-<li><a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut/kk</em></a></li>
-<li><a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut/omp</em></a></li>
-<li><a class="reference internal" href="pair_lj.html"><em>pair_style lj/cut/opt</em></a></li>
-</ul>
-<p>To see what accelerate styles are currently available, see
-<a class="reference internal" href="Section_commands.html#cmd-5"><span>Section_commands 5</span></a> of the manual.  The
-doc pages for individual commands (e.g. <a class="reference internal" href="pair_lj.html"><em>pair lj/cut</em></a> or
-<a class="reference internal" href="fix_nve.html"><em>fix nve</em></a>) also list any accelerated variants available
-for that style.</p>
-<p>To use an accelerator package in LAMMPS, and one or more of the styles
-it provides, follow these general steps.  Details vary from package to
-package and are explained in the individual accelerator doc pages,
-listed above:</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="26%" />
-<col width="74%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td>build the accelerator library</td>
-<td>only for USER-CUDA and GPU packages</td>
-</tr>
-<tr class="row-even"><td>install the accelerator package</td>
-<td>make yes-opt, make yes-user-intel, etc</td>
-</tr>
-</tbody>
-</table>
-<div class="line-block">
-<div class="line">install the accelerator package             | make yes-opt, make yes-user-intel, etc                                                                                           |</div>
-</div>
-<blockquote>
-<div>only for USER-INTEL, KOKKOS, USER-OMP, OPT packages                                                          |</div></blockquote>
-<table border="1" class="docutils">
-<colgroup>
-<col width="26%" />
-<col width="74%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td>re-build LAMMPS</td>
-<td>make machine</td>
-</tr>
-</tbody>
-</table>
-<div class="line-block">
-<div class="line">re-build LAMMPS                             | make machine                                                                                                                     |</div>
-</div>
-<blockquote>
-<div>mpirun -np 32 lmp_machine -in in.script                                                          |</div></blockquote>
-<blockquote>
-<div>only for USER-CUDA and KOKKOS packages                    |</div></blockquote>
-<blockquote>
-<div><a class="reference internal" href="package.html"><em>package</em></a> command, &lt;br&gt;
-only if defaults need to be changed |</div></blockquote>
-<blockquote>
-<div><a class="reference internal" href="suffix.html"><em>suffix</em></a> command                                               |</div></blockquote>
-<table border="1" class="docutils">
-<colgroup>
-</colgroup>
-<tbody valign="top">
-</tbody>
-</table>
-<p>Note that the first 4 steps can be done as a single command, using the
-src/Make.py tool.  This tool is discussed in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual, and its use is
-illustrated in the individual accelerator sections.  Typically these
-steps only need to be done once, to create an executable that uses one
-or more accelerator packages.</p>
-<p>The last 4 steps can all be done from the command-line when LAMMPS is
-launched, without changing your input script, as illustrated in the
-individual accelerator sections.  Or you can add
-<a class="reference internal" href="package.html"><em>package</em></a> and <a class="reference internal" href="suffix.html"><em>suffix</em></a> commands to your input
-script.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">With a few exceptions, you can build a single LAMMPS
-executable with all its accelerator packages installed.  Note however
-that the USER-INTEL and KOKKOS packages require you to choose one of
-their hardware options when building for a specific platform.
-I.e. CPU or Phi option for the USER-INTEL package.  Or the OpenMP,
-Cuda, or Phi option for the KOKKOS package.</p>
-</div>
-<p>These are the exceptions.  You cannot build a single executable with:</p>
-<ul class="simple">
-<li>both the USER-INTEL Phi and KOKKOS Phi options</li>
-<li>the USER-INTEL Phi or Kokkos Phi option, and either the USER-CUDA or GPU packages</li>
-</ul>
-<p>See the examples/accelerate/README and make.list files for sample
-Make.py commands that build LAMMPS with any or all of the accelerator
-packages.  As an example, here is a command that builds with all the
-GPU related packages installed (USER-CUDA, GPU, KOKKOS with Cuda),
-including settings to build the needed auxiliary USER-CUDA and GPU
-libraries for Kepler GPUs:</p>
-<pre class="literal-block">
-Make.py -j 16 -p omp gpu cuda kokkos -cc nvcc wrap=mpi   -cuda mode=double arch=35 -gpu mode=double arch=35  -kokkos cuda arch=35 lib-all file mpi
-</pre>
-<p>The examples/accelerate directory also has input scripts that can be
-used with all of the accelerator packages.  See its README file for
-details.</p>
-<p>Likewise, the bench directory has FERMI and KEPLER and PHI
-sub-directories with Make.py commands and input scripts for using all
-the accelerator packages on various machines.  See the README files in
-those dirs.</p>
-<p>As mentioned above, the <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the LAMMPS web site gives
-performance results for the various accelerator packages for several
-of the standard LAMMPS benchmark problems, as a function of problem
-size and number of compute nodes, on different hardware platforms.</p>
-<p>Here is a brief summary of what the various packages provide.  Details
-are in the individual accelerator sections.</p>
-<ul class="simple">
-<li>Styles with a &#8220;cuda&#8221; or &#8220;gpu&#8221; suffix are part of the USER-CUDA or GPU
-packages, and can be run on NVIDIA GPUs.  The speed-up on a GPU
-depends on a variety of factors, discussed in the accelerator
-sections.</li>
-<li>Styles with an &#8220;intel&#8221; suffix are part of the USER-INTEL
-package. These styles support vectorized single and mixed precision
-calculations, in addition to full double precision.  In extreme cases,
-this can provide speedups over 3.5x on CPUs.  The package also
-supports acceleration in &#8220;offload&#8221; mode to Intel(R) Xeon Phi(TM)
-coprocessors.  This can result in additional speedup over 2x depending
-on the hardware configuration.</li>
-<li>Styles with a &#8220;kk&#8221; suffix are part of the KOKKOS package, and can be
-run using OpenMP on multicore CPUs, on an NVIDIA GPU, or on an Intel
-Xeon Phi in &#8220;native&#8221; mode.  The speed-up depends on a variety of
-factors, as discussed on the KOKKOS accelerator page.</li>
-<li>Styles with an &#8220;omp&#8221; suffix are part of the USER-OMP package and allow
-a pair-style to be run in multi-threaded mode using OpenMP.  This can
-be useful on nodes with high-core counts when using less MPI processes
-than cores is advantageous, e.g. when running with PPPM so that FFTs
-are run on fewer MPI processors or when the many MPI tasks would
-overload the available bandwidth for communication.</li>
-<li>Styles with an &#8220;opt&#8221; suffix are part of the OPT package and typically
-speed-up the pairwise calculations of your simulation by 5-25% on a
-CPU.</li>
-</ul>
-<p>The individual accelerator package doc pages explain:</p>
-<ul class="simple">
-<li>what hardware and software the accelerated package requires</li>
-<li>how to build LAMMPS with the accelerated package</li>
-<li>how to run with the accelerated package either via command-line switches or modifying the input script</li>
-<li>speed-ups to expect</li>
-<li>guidelines for best performance</li>
-<li>restrictions</li>
-</ul>
-<hr class="docutils" />
-</div>
-<div class="section" id="comparison-of-various-accelerator-packages">
-<span id="acc-4"></span><h2>5.4. Comparison of various accelerator packages<a class="headerlink" href="#comparison-of-various-accelerator-packages" title="Permalink to this headline">¶</a></h2>
-<div class="admonition note">
-<p class="first admonition-title">Note</p>
-<p class="last">this section still needs to be re-worked with additional KOKKOS
-and USER-INTEL information.</p>
-</div>
-<p>The next section compares and contrasts the various accelerator
-options, since there are multiple ways to perform OpenMP threading,
-run on GPUs, and run on Intel Xeon Phi coprocessors.</p>
-<p>All 3 of these packages accelerate a LAMMPS calculation using NVIDIA
-hardware, but they do it in different ways.</p>
-<p>As a consequence, for a particular simulation on specific hardware,
-one package may be faster than the other.  We give guidelines below,
-but the best way to determine which package is faster for your input
-script is to try both of them on your machine.  See the benchmarking
-section below for examples where this has been done.</p>
-<p><strong>Guidelines for using each package optimally:</strong></p>
-<ul class="simple">
-<li>The GPU package allows you to assign multiple CPUs (cores) to a single
-GPU (a common configuration for &#8220;hybrid&#8221; nodes that contain multicore
-CPU(s) and GPU(s)) and works effectively in this mode.  The USER-CUDA
-package does not allow this; you can only use one CPU per GPU.</li>
-<li>The GPU package moves per-atom data (coordinates, forces)
-back-and-forth between the CPU and GPU every timestep.  The USER-CUDA
-package only does this on timesteps when a CPU calculation is required
-(e.g. to invoke a fix or compute that is non-GPU-ized).  Hence, if you
-can formulate your input script to only use GPU-ized fixes and
-computes, and avoid doing I/O too often (thermo output, dump file
-snapshots, restart files), then the data transfer cost of the
-USER-CUDA package can be very low, causing it to run faster than the
-GPU package.</li>
-<li>The GPU package is often faster than the USER-CUDA package, if the
-number of atoms per GPU is smaller.  The crossover point, in terms of
-atoms/GPU at which the USER-CUDA package becomes faster depends
-strongly on the pair style.  For example, for a simple Lennard Jones
-system the crossover (in single precision) is often about 50K-100K
-atoms per GPU.  When performing double precision calculations the
-crossover point can be significantly smaller.</li>
-<li>Both packages compute bonded interactions (bonds, angles, etc) on the
-CPU.  This means a model with bonds will force the USER-CUDA package
-to transfer per-atom data back-and-forth between the CPU and GPU every
-timestep.  If the GPU package is running with several MPI processes
-assigned to one GPU, the cost of computing the bonded interactions is
-spread across more CPUs and hence the GPU package can run faster.</li>
-<li>When using the GPU package with multiple CPUs assigned to one GPU, its
-performance depends to some extent on high bandwidth between the CPUs
-and the GPU.  Hence its performance is affected if full 16 PCIe lanes
-are not available for each GPU.  In HPC environments this can be the
-case if S2050/70 servers are used, where two devices generally share
-one PCIe 2.0 16x slot.  Also many multi-GPU mainboards do not provide
-full 16 lanes to each of the PCIe 2.0 16x slots.</li>
-</ul>
-<p><strong>Differences between the two packages:</strong></p>
-<ul class="simple">
-<li>The GPU package accelerates only pair force, neighbor list, and PPPM
-calculations.  The USER-CUDA package currently supports a wider range
-of pair styles and can also accelerate many fix styles and some
-compute styles, as well as neighbor list and PPPM calculations.</li>
-<li>The USER-CUDA package does not support acceleration for minimization.</li>
-<li>The USER-CUDA package does not support hybrid pair styles.</li>
-<li>The USER-CUDA package can order atoms in the neighbor list differently
-from run to run resulting in a different order for force accumulation.</li>
-<li>The USER-CUDA package has a limit on the number of atom types that can be
-used in a simulation.</li>
-<li>The GPU package requires neighbor lists to be built on the CPU when using
-exclusion lists or a triclinic simulation box.</li>
-<li>The GPU package uses more GPU memory than the USER-CUDA package.  This
-is generally not a problem since typical runs are computation-limited
-rather than memory-limited.</li>
-</ul>
-<div class="section" id="examples">
-<h3>5.4.1. Examples<a class="headerlink" href="#examples" title="Permalink to this headline">¶</a></h3>
-<p>The LAMMPS distribution has two directories with sample input scripts
-for the GPU and USER-CUDA packages.</p>
-<ul class="simple">
-<li>lammps/examples/gpu = GPU package files</li>
-<li>lammps/examples/USER/cuda = USER-CUDA package files</li>
-</ul>
-<p>These contain input scripts for identical systems, so they can be used
-to benchmark the performance of both packages on your system.</p>
-</div>
-</div>
-</div>
-
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doc/Section_accelerate.txt

@@ -1,415 +0,0 @@
-"Previous Section"_Section_packages.html - "LAMMPS WWW Site"_lws -
-"LAMMPS Documentation"_ld - "LAMMPS Commands"_lc - "Next
-Section"_Section_howto.html :c
-
-:link(lws,http://lammps.sandia.gov)
-:link(ld,Manual.html)
-:link(lc,Section_commands.html#comm)
-
-:line
-
-5. Accelerating LAMMPS performance :h3
-
-This section describes various methods for improving LAMMPS
-performance for different classes of problems running on different
-kinds of machines.
-
-There are two thrusts to the discussion that follows.  The
-first is using code options that implement alternate algorithms
-that can speed-up a simulation.  The second is to use one
-of the several accelerator packages provided with LAMMPS that
-contain code optimized for certain kinds of hardware, including
-multi-core CPUs, GPUs, and Intel Xeon Phi coprocessors.
-
-5.1 "Measuring performance"_#acc_1 :ulb,l
-5.2 "Algorithms and code options to boost performace"_#acc_2 :l
-5.3 "Accelerator packages with optimized styles"_#acc_3 :l
-    5.3.1 "USER-CUDA package"_accelerate_cuda.html :ulb,l
-    5.3.2 "GPU package"_accelerate_gpu.html :l
-    5.3.3 "USER-INTEL package"_accelerate_intel.html :l
-    5.3.4 "KOKKOS package"_accelerate_kokkos.html :l
-    5.3.5 "USER-OMP package"_accelerate_omp.html :l
-    5.3.6 "OPT package"_accelerate_opt.html :l,ule
-5.4 "Comparison of various accelerator packages"_#acc_4 :l,ule
-
-The "Benchmark page"_http://lammps.sandia.gov/bench.html of the LAMMPS
-web site gives performance results for the various accelerator
-packages discussed in Section 5.2, for several of the standard LAMMPS
-benchmark problems, as a function of problem size and number of
-compute nodes, on different hardware platforms.
-
-:line
-:line
-
-5.1 Measuring performance :h4,link(acc_1)
-
-Before trying to make your simulation run faster, you should
-understand how it currently performs and where the bottlenecks are.
-
-The best way to do this is run the your system (actual number of
-atoms) for a modest number of timesteps (say 100 steps) on several
-different processor counts, including a single processor if possible.
-Do this for an equilibrium version of your system, so that the
-100-step timings are representative of a much longer run.  There is
-typically no need to run for 1000s of timesteps to get accurate
-timings; you can simply extrapolate from short runs.
-
-For the set of runs, look at the timing data printed to the screen and
-log file at the end of each LAMMPS run.  "This
-section"_Section_start.html#start_8 of the manual has an overview.
-
-Running on one (or a few processors) should give a good estimate of
-the serial performance and what portions of the timestep are taking
-the most time.  Running the same problem on a few different processor
-counts should give an estimate of parallel scalability.  I.e. if the
-simulation runs 16x faster on 16 processors, its 100% parallel
-efficient; if it runs 8x faster on 16 processors, it's 50% efficient.
-
-The most important data to look at in the timing info is the timing
-breakdown and relative percentages.  For example, trying different
-options for speeding up the long-range solvers will have little impact
-if they only consume 10% of the run time.  If the pairwise time is
-dominating, you may want to look at GPU or OMP versions of the pair
-style, as discussed below.  Comparing how the percentages change as
-you increase the processor count gives you a sense of how different
-operations within the timestep are scaling.  Note that if you are
-running with a Kspace solver, there is additional output on the
-breakdown of the Kspace time.  For PPPM, this includes the fraction
-spent on FFTs, which can be communication intensive.
-
-Another important detail in the timing info are the histograms of
-atoms counts and neighbor counts.  If these vary widely across
-processors, you have a load-imbalance issue.  This often results in
-inaccurate relative timing data, because processors have to wait when
-communication occurs for other processors to catch up.  Thus the
-reported times for "Communication" or "Other" may be higher than they
-really are, due to load-imbalance.  If this is an issue, you can
-uncomment the MPI_Barrier() lines in src/timer.cpp, and recompile
-LAMMPS, to obtain synchronized timings.
-
-:line
-
-5.2 General strategies :h4,link(acc_2)
-
-NOTE: this section 5.2 is still a work in progress
-
-Here is a list of general ideas for improving simulation performance.
-Most of them are only applicable to certain models and certain
-bottlenecks in the current performance, so let the timing data you
-generate be your guide.  It is hard, if not impossible, to predict how
-much difference these options will make, since it is a function of
-problem size, number of processors used, and your machine.  There is
-no substitute for identifying performance bottlenecks, and trying out
-various options.
-
-rRESPA
-2-FFT PPPM
-Staggered PPPM
-single vs double PPPM
-partial charge PPPM
-verlet/split run style
-processor command for proc layout and numa layout
-load-balancing: balance and fix balance :ul
-
-2-FFT PPPM, also called {analytic differentiation} or {ad} PPPM, uses
-2 FFTs instead of the 4 FFTs used by the default {ik differentiation}
-PPPM. However, 2-FFT PPPM also requires a slightly larger mesh size to
-achieve the same accuracy as 4-FFT PPPM. For problems where the FFT
-cost is the performance bottleneck (typically large problems running
-on many processors), 2-FFT PPPM may be faster than 4-FFT PPPM.
-  
-Staggered PPPM performs calculations using two different meshes, one
-shifted slightly with respect to the other.  This can reduce force
-aliasing errors and increase the accuracy of the method, but also
-doubles the amount of work required. For high relative accuracy, using
-staggered PPPM allows one to half the mesh size in each dimension as
-compared to regular PPPM, which can give around a 4x speedup in the
-kspace time. However, for low relative accuracy, using staggered PPPM
-gives little benefit and can be up to 2x slower in the kspace
-time. For example, the rhodopsin benchmark was run on a single
-processor, and results for kspace time vs. relative accuracy for the
-different methods are shown in the figure below.  For this system,
-staggered PPPM (using ik differentiation) becomes useful when using a
-relative accuracy of slightly greater than 1e-5 and above.
-
-:c,image(JPG/rhodo_staggered.jpg)
-
-IMPORTANT NOTE: Using staggered PPPM may not give the same increase in
-accuracy of energy and pressure as it does in forces, so some caution
-must be used if energy and/or pressure are quantities of interest,
-such as when using a barostat.
-
-:line
-
-5.3 Packages with optimized styles :h4,link(acc_3)
-
-Accelerated versions of various "pair_style"_pair_style.html,
-"fixes"_fix.html, "computes"_compute.html, and other commands have
-been added to LAMMPS, which will typically run faster than the
-standard non-accelerated versions.  Some require appropriate hardware
-to be present on your system, e.g. GPUs or Intel Xeon Phi
-coprocessors.
-
-All of these commands are in packages provided with LAMMPS.  An
-overview of packages is give in "Section
-packages"_Section_packages.html.
-
-These are the accelerator packages
-currently in LAMMPS, either as standard or user packages:
-
-"USER-CUDA"_accelerate_cuda.html : for NVIDIA GPUs
-"GPU"_accelerate_gpu.html : for NVIDIA GPUs as well as OpenCL support
-"USER-INTEL"_accelerate_intel.html : for Intel CPUs and Intel Xeon Phi
-"KOKKOS"_accelerate_kokkos.html : for GPUs, Intel Xeon Phi, and OpenMP threading
-"USER-OMP"_accelerate_omp.html : for OpenMP threading
-"OPT"_accelerate_opt.html : generic CPU optimizations :tb(s=:)
-
-Inverting this list, LAMMPS currently has acceleration support for
-three kinds of hardware, via the listed packages:
-
-Many-core CPUs : "USER-INTEL"_accelerate_intel.html, "KOKKOS"_accelerate_kokkos.html, "USER-OMP"_accelerate_omp.html, "OPT"_accelerate_opt.html packages
-NVIDIA GPUs : "USER-CUDA"_accelerate_cuda.html, "GPU"_accelerate_gpu.html, "KOKKOS"_accelerate_kokkos.html packages
-Intel Phi : "USER-INTEL"_accelerate_intel.html, "KOKKOS"_accelerate_kokkos.html packages :tb(s=:)
-
-Which package is fastest for your hardware may depend on the size
-problem you are running and what commands (accelerated and
-non-accelerated) are invoked by your input script.  While these doc
-pages include performance guidelines, there is no substitute for
-trying out the different packages appropriate to your hardware.
-
-Any accelerated style has the same name as the corresponding standard
-style, except that a suffix is appended.  Otherwise, the syntax for
-the command that uses the style is identical, their functionality is
-the same, and the numerical results it produces should also be the
-same, except for precision and round-off effects.
-
-For example, all of these styles are accelerated variants of the
-Lennard-Jones "pair_style lj/cut"_pair_lj.html:
-
-"pair_style lj/cut/cuda"_pair_lj.html
-"pair_style lj/cut/gpu"_pair_lj.html
-"pair_style lj/cut/intel"_pair_lj.html
-"pair_style lj/cut/kk"_pair_lj.html
-"pair_style lj/cut/omp"_pair_lj.html
-"pair_style lj/cut/opt"_pair_lj.html :ul
-
-To see what accelerate styles are currently available, see
-"Section_commands 5"_Section_commands.html#cmd_5 of the manual.  The
-doc pages for individual commands (e.g. "pair lj/cut"_pair_lj.html or
-"fix nve"_fix_nve.html) also list any accelerated variants available
-for that style.
-
-To use an accelerator package in LAMMPS, and one or more of the styles
-it provides, follow these general steps.  Details vary from package to
-package and are explained in the individual accelerator doc pages,
-listed above:
-
-build the accelerator library |
-  only for USER-CUDA and GPU packages |
-install the accelerator package |
-  make yes-opt, make yes-user-intel, etc |
-add compile/link flags to Makefile.machine |
-  in src/MAKE, <br>
-  only for USER-INTEL, KOKKOS, USER-OMP, OPT packages |
-re-build LAMMPS |
-  make machine |
-run a LAMMPS simulation |
-  lmp_machine < in.script <br> 
-  mpirun -np 32 lmp_machine -in in.script |
-enable the accelerator package |
-  via "-c on" and "-k on" "command-line switches"_Section_start.html#start_7, <br>
-  only for USER-CUDA and KOKKOS packages |
-set any needed options for the package |
-  via "-pk" "command-line switch"_Section_start.html#start_7 or
-  "package"_package.html command, <br>
-  only if defaults need to be changed |
-use accelerated styles in your input script |
-  via "-sf" "command-line switch"_Section_start.html#start_7 or
-  "suffix"_suffix.html command :tb(c=2,s=|)
-
-Note that the first 4 steps can be done as a single command, using the
-src/Make.py tool.  This tool is discussed in "Section
-2.4"_Section_start.html#start_4 of the manual, and its use is
-illustrated in the individual accelerator sections.  Typically these
-steps only need to be done once, to create an executable that uses one
-or more accelerator packages.
-
-The last 4 steps can all be done from the command-line when LAMMPS is
-launched, without changing your input script, as illustrated in the
-individual accelerator sections.  Or you can add
-"package"_package.html and "suffix"_suffix.html commands to your input
-script.
-
-IMPORTANT NOTE: With a few exceptions, you can build a single LAMMPS
-executable with all its accelerator packages installed.  Note however
-that the USER-INTEL and KOKKOS packages require you to choose one of
-their hardware options when building for a specific platform.
-I.e. CPU or Phi option for the USER-INTEL package.  Or the OpenMP,
-Cuda, or Phi option for the KOKKOS package.
-
-These are the exceptions.  You cannot build a single executable with:
-
-both the USER-INTEL Phi and KOKKOS Phi options
-the USER-INTEL Phi or Kokkos Phi option, and either the USER-CUDA or GPU packages :ul
-
-See the examples/accelerate/README and make.list files for sample
-Make.py commands that build LAMMPS with any or all of the accelerator
-packages.  As an example, here is a command that builds with all the
-GPU related packages installed (USER-CUDA, GPU, KOKKOS with Cuda),
-including settings to build the needed auxiliary USER-CUDA and GPU
-libraries for Kepler GPUs:
-
-Make.py -j 16 -p omp gpu cuda kokkos -cc nvcc wrap=mpi \
-  -cuda mode=double arch=35 -gpu mode=double arch=35 \\
-  -kokkos cuda arch=35 lib-all file mpi :pre
-
-The examples/accelerate directory also has input scripts that can be
-used with all of the accelerator packages.  See its README file for
-details.
-
-Likewise, the bench directory has FERMI and KEPLER and PHI
-sub-directories with Make.py commands and input scripts for using all
-the accelerator packages on various machines.  See the README files in
-those dirs.
-
-As mentioned above, the "Benchmark
-page"_http://lammps.sandia.gov/bench.html of the LAMMPS web site gives
-performance results for the various accelerator packages for several
-of the standard LAMMPS benchmark problems, as a function of problem
-size and number of compute nodes, on different hardware platforms.
-
-Here is a brief summary of what the various packages provide.  Details
-are in the individual accelerator sections.
-
-Styles with a "cuda" or "gpu" suffix are part of the USER-CUDA or GPU
-packages, and can be run on NVIDIA GPUs.  The speed-up on a GPU
-depends on a variety of factors, discussed in the accelerator
-sections. :ulb,l
-
-Styles with an "intel" suffix are part of the USER-INTEL
-package. These styles support vectorized single and mixed precision
-calculations, in addition to full double precision.  In extreme cases,
-this can provide speedups over 3.5x on CPUs.  The package also
-supports acceleration in "offload" mode to Intel(R) Xeon Phi(TM)
-coprocessors.  This can result in additional speedup over 2x depending
-on the hardware configuration. :l
-
-Styles with a "kk" suffix are part of the KOKKOS package, and can be
-run using OpenMP on multicore CPUs, on an NVIDIA GPU, or on an Intel
-Xeon Phi in "native" mode.  The speed-up depends on a variety of
-factors, as discussed on the KOKKOS accelerator page. :l
-
-Styles with an "omp" suffix are part of the USER-OMP package and allow
-a pair-style to be run in multi-threaded mode using OpenMP.  This can
-be useful on nodes with high-core counts when using less MPI processes
-than cores is advantageous, e.g. when running with PPPM so that FFTs
-are run on fewer MPI processors or when the many MPI tasks would
-overload the available bandwidth for communication. :l
-
-Styles with an "opt" suffix are part of the OPT package and typically
-speed-up the pairwise calculations of your simulation by 5-25% on a
-CPU. :l,ule
-
-The individual accelerator package doc pages explain:
-
-what hardware and software the accelerated package requires
-how to build LAMMPS with the accelerated package
-how to run with the accelerated package either via command-line switches or modifying the input script
-speed-ups to expect
-guidelines for best performance
-restrictions :ul
-
-:line
-
-5.4 Comparison of various accelerator packages :h4,link(acc_4)
-
-NOTE: this section still needs to be re-worked with additional KOKKOS
-and USER-INTEL information.
-
-The next section compares and contrasts the various accelerator
-options, since there are multiple ways to perform OpenMP threading,
-run on GPUs, and run on Intel Xeon Phi coprocessors.
-
-All 3 of these packages accelerate a LAMMPS calculation using NVIDIA
-hardware, but they do it in different ways.
-
-As a consequence, for a particular simulation on specific hardware,
-one package may be faster than the other.  We give guidelines below,
-but the best way to determine which package is faster for your input
-script is to try both of them on your machine.  See the benchmarking
-section below for examples where this has been done.
-
-[Guidelines for using each package optimally:]
-
-The GPU package allows you to assign multiple CPUs (cores) to a single
-GPU (a common configuration for "hybrid" nodes that contain multicore
-CPU(s) and GPU(s)) and works effectively in this mode.  The USER-CUDA
-package does not allow this; you can only use one CPU per GPU. :ulb,l
-
-The GPU package moves per-atom data (coordinates, forces)
-back-and-forth between the CPU and GPU every timestep.  The USER-CUDA
-package only does this on timesteps when a CPU calculation is required
-(e.g. to invoke a fix or compute that is non-GPU-ized).  Hence, if you
-can formulate your input script to only use GPU-ized fixes and
-computes, and avoid doing I/O too often (thermo output, dump file
-snapshots, restart files), then the data transfer cost of the
-USER-CUDA package can be very low, causing it to run faster than the
-GPU package. :l
-
-The GPU package is often faster than the USER-CUDA package, if the
-number of atoms per GPU is smaller.  The crossover point, in terms of
-atoms/GPU at which the USER-CUDA package becomes faster depends
-strongly on the pair style.  For example, for a simple Lennard Jones
-system the crossover (in single precision) is often about 50K-100K
-atoms per GPU.  When performing double precision calculations the
-crossover point can be significantly smaller. :l
-
-Both packages compute bonded interactions (bonds, angles, etc) on the
-CPU.  This means a model with bonds will force the USER-CUDA package
-to transfer per-atom data back-and-forth between the CPU and GPU every
-timestep.  If the GPU package is running with several MPI processes
-assigned to one GPU, the cost of computing the bonded interactions is
-spread across more CPUs and hence the GPU package can run faster. :l
-
-When using the GPU package with multiple CPUs assigned to one GPU, its
-performance depends to some extent on high bandwidth between the CPUs
-and the GPU.  Hence its performance is affected if full 16 PCIe lanes
-are not available for each GPU.  In HPC environments this can be the
-case if S2050/70 servers are used, where two devices generally share
-one PCIe 2.0 16x slot.  Also many multi-GPU mainboards do not provide
-full 16 lanes to each of the PCIe 2.0 16x slots. :l,ule
-
-[Differences between the two packages:]
-
-The GPU package accelerates only pair force, neighbor list, and PPPM
-calculations.  The USER-CUDA package currently supports a wider range
-of pair styles and can also accelerate many fix styles and some
-compute styles, as well as neighbor list and PPPM calculations. :ulb,l
-
-The USER-CUDA package does not support acceleration for minimization. :l
-
-The USER-CUDA package does not support hybrid pair styles. :l
-
-The USER-CUDA package can order atoms in the neighbor list differently
-from run to run resulting in a different order for force accumulation. :l
-
-The USER-CUDA package has a limit on the number of atom types that can be
-used in a simulation. :l
-
-The GPU package requires neighbor lists to be built on the CPU when using
-exclusion lists or a triclinic simulation box. :l
-
-The GPU package uses more GPU memory than the USER-CUDA package.  This
-is generally not a problem since typical runs are computation-limited
-rather than memory-limited. :l,ule
-
-[Examples:]
-
-The LAMMPS distribution has two directories with sample input scripts
-for the GPU and USER-CUDA packages.
-
-lammps/examples/gpu = GPU package files
-lammps/examples/USER/cuda = USER-CUDA package files :ul
-
-These contain input scripts for identical systems, so they can be used
-to benchmark the performance of both packages on your system.

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-  <div class="section" id="example-problems">
-<h1>7. Example problems<a class="headerlink" href="#example-problems" title="Permalink to this headline">¶</a></h1>
-<p>The LAMMPS distribution includes an examples sub-directory with
-several sample problems.  Each problem is in a sub-directory of its
-own.  Most are 2d models so that they run quickly, requiring at most a
-couple of minutes to run on a desktop machine.  Each problem has an
-input script (in.*) and produces a log file (log.*) and dump file
-(dump.*) when it runs.  Some use a data file (data.*) of initial
-coordinates as additional input.  A few sample log file outputs on
-different machines and different numbers of processors are included in
-the directories to compare your answers to.  E.g. a log file like
-log.crack.foo.P means it ran on P processors of machine &#8220;foo&#8221;.</p>
-<p>For examples that use input data files, many of them were produced by
-<a class="reference external" href="http://pizza.sandia.gov">Pizza.py</a> or setup tools described in the
-<a class="reference internal" href="Section_tools.html"><em>Additional Tools</em></a> section of the LAMMPS
-documentation and provided with the LAMMPS distribution.</p>
-<p>If you uncomment the <a class="reference internal" href="dump.html"><em>dump</em></a> command in the input script, a
-text dump file will be produced, which can be animated by various
-<a class="reference external" href="http://lammps.sandia.gov/viz.html">visualization programs</a>.  It can
-also be animated using the xmovie tool described in the <a class="reference internal" href="Section_tools.html"><em>Additional Tools</em></a> section of the LAMMPS documentation.</p>
-<p>If you uncomment the <a class="reference internal" href="dump.html"><em>dump image</em></a> command in the input
-script, and assuming you have built LAMMPS with a JPG library, JPG
-snapshot images will be produced when the simulation runs.  They can
-be quickly post-processed into a movie using commands described on the
-<a class="reference internal" href="dump_image.html"><em>dump image</em></a> doc page.</p>
-<p>Animations of many of these examples can be viewed on the Movies
-section of the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>.</p>
-<p>These are the sample problems in the examples sub-directories:</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="15%" />
-<col width="85%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td>balance</td>
-<td>dynamic load balancing, 2d system</td>
-</tr>
-<tr class="row-even"><td>body</td>
-<td>body particles, 2d system</td>
-</tr>
-<tr class="row-odd"><td>colloid</td>
-<td>big colloid particles in a small particle solvent, 2d system</td>
-</tr>
-<tr class="row-even"><td>comb</td>
-<td>models using the COMB potential</td>
-</tr>
-<tr class="row-odd"><td>crack</td>
-<td>crack propagation in a 2d solid</td>
-</tr>
-<tr class="row-even"><td>cuda</td>
-<td>use of the USER-CUDA package for GPU acceleration</td>
-</tr>
-<tr class="row-odd"><td>dipole</td>
-<td>point dipolar particles, 2d system</td>
-</tr>
-<tr class="row-even"><td>dreiding</td>
-<td>methanol via Dreiding FF</td>
-</tr>
-<tr class="row-odd"><td>eim</td>
-<td>NaCl using the EIM potential</td>
-</tr>
-<tr class="row-even"><td>ellipse</td>
-<td>ellipsoidal particles in spherical solvent, 2d system</td>
-</tr>
-<tr class="row-odd"><td>flow</td>
-<td>Couette and Poiseuille flow in a 2d channel</td>
-</tr>
-<tr class="row-even"><td>friction</td>
-<td>frictional contact of spherical asperities between 2d surfaces</td>
-</tr>
-<tr class="row-odd"><td>gpu</td>
-<td>use of the GPU package for GPU acceleration</td>
-</tr>
-<tr class="row-even"><td>hugoniostat</td>
-<td>Hugoniostat shock dynamics</td>
-</tr>
-<tr class="row-odd"><td>indent</td>
-<td>spherical indenter into a 2d solid</td>
-</tr>
-<tr class="row-even"><td>intel</td>
-<td>use of the USER-INTEL package for CPU or Intel(R) Xeon Phi(TM) coprocessor</td>
-</tr>
-<tr class="row-odd"><td>kim</td>
-<td>use of potentials in Knowledge Base for Interatomic Models (KIM)</td>
-</tr>
-<tr class="row-even"><td>line</td>
-<td>line segment particles in 2d rigid bodies</td>
-</tr>
-<tr class="row-odd"><td>meam</td>
-<td>MEAM test for SiC and shear (same as shear examples)</td>
-</tr>
-<tr class="row-even"><td>melt</td>
-<td>rapid melt of 3d LJ system</td>
-</tr>
-<tr class="row-odd"><td>micelle</td>
-<td>self-assembly of small lipid-like molecules into 2d bilayers</td>
-</tr>
-<tr class="row-even"><td>min</td>
-<td>energy minimization of 2d LJ melt</td>
-</tr>
-<tr class="row-odd"><td>msst</td>
-<td>MSST shock dynamics</td>
-</tr>
-<tr class="row-even"><td>nb3b</td>
-<td>use of nonbonded 3-body harmonic pair style</td>
-</tr>
-<tr class="row-odd"><td>neb</td>
-<td>nudged elastic band (NEB) calculation for barrier finding</td>
-</tr>
-<tr class="row-even"><td>nemd</td>
-<td>non-equilibrium MD of 2d sheared system</td>
-</tr>
-<tr class="row-odd"><td>obstacle</td>
-<td>flow around two voids in a 2d channel</td>
-</tr>
-<tr class="row-even"><td>peptide</td>
-<td>dynamics of a small solvated peptide chain (5-mer)</td>
-</tr>
-<tr class="row-odd"><td>peri</td>
-<td>Peridynamic model of cylinder impacted by indenter</td>
-</tr>
-<tr class="row-even"><td>pour</td>
-<td>pouring of granular particles into a 3d box, then chute flow</td>
-</tr>
-<tr class="row-odd"><td>prd</td>
-<td>parallel replica dynamics of vacancy diffusion in bulk Si</td>
-</tr>
-<tr class="row-even"><td>qeq</td>
-<td>use of the QEQ pacakge for charge equilibration</td>
-</tr>
-<tr class="row-odd"><td>reax</td>
-<td>RDX and TATB models using the ReaxFF</td>
-</tr>
-<tr class="row-even"><td>rigid</td>
-<td>rigid bodies modeled as independent or coupled</td>
-</tr>
-<tr class="row-odd"><td>shear</td>
-<td>sideways shear applied to 2d solid, with and without a void</td>
-</tr>
-<tr class="row-even"><td>snap</td>
-<td>NVE dynamics for BCC tantalum crystal using SNAP potential</td>
-</tr>
-<tr class="row-odd"><td>srd</td>
-<td>stochastic rotation dynamics (SRD) particles as solvent</td>
-</tr>
-<tr class="row-even"><td>tad</td>
-<td>temperature-accelerated dynamics of vacancy diffusion in bulk Si</td>
-</tr>
-<tr class="row-odd"><td>tri</td>
-<td>triangular particles in rigid bodies</td>
-</tr>
-</tbody>
-</table>
-<p>vashishta: models using the Vashishta potential</p>
-<p>Here is how you might run and visualize one of the sample problems:</p>
-<div class="highlight-python"><div class="highlight"><pre>cd indent
-cp ../../src/lmp_linux .           # copy LAMMPS executable to this dir
-lmp_linux -in in.indent            # run the problem
-</pre></div>
-</div>
-<p>Running the simulation produces the files <em>dump.indent</em> and
-<em>log.lammps</em>.  You can visualize the dump file as follows:</p>
-<div class="highlight-python"><div class="highlight"><pre>../../tools/xmovie/xmovie -scale dump.indent
-</pre></div>
-</div>
-<p>If you uncomment the <a class="reference internal" href="dump_image.html"><em>dump image</em></a> line(s) in the input
-script a series of JPG images will be produced by the run.  These can
-be viewed individually or turned into a movie or animated by tools
-like ImageMagick or QuickTime or various Windows-based tools.  See the
-<a class="reference internal" href="dump_image.html"><em>dump image</em></a> doc page for more details.  E.g. this
-Imagemagick command would create a GIF file suitable for viewing in a
-browser.</p>
-<div class="highlight-python"><div class="highlight"><pre>% convert -loop 1 *.jpg foo.gif
-</pre></div>
-</div>
-<hr class="docutils" />
-<p>There is also a COUPLE directory with examples of how to use LAMMPS as
-a library, either by itself or in tandem with another code or library.
-See the COUPLE/README file to get started.</p>
-<p>There is also an ELASTIC directory with an example script for
-computing elastic constants at zero temperature, using an Si example.  See
-the ELASTIC/in.elastic file for more info.</p>
-<p>There is also an ELASTIC_T directory with an example script for
-computing elastic constants at finite temperature, using an Si example.  See
-the ELASTIC_T/in.elastic file for more info.</p>
-<p>There is also a USER directory which contains subdirectories of
-user-provided examples for user packages.  See the README files in
-those directories for more info.  See the
-<a class="reference internal" href="Section_start.html"><em>Section_start.html</em></a> file for more info about user
-packages.</p>
-</div>
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doc/Section_example.txt

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-"Previous Section"_Section_howto.html - "LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc - "Next Section"_Section_perf.html :c
-
-:link(lws,http://lammps.sandia.gov)
-:link(ld,Manual.html)
-:link(lc,Section_commands.html#comm)
-
-:line
-
-7. Example problems :h3
-
-The LAMMPS distribution includes an examples sub-directory with
-several sample problems.  Each problem is in a sub-directory of its
-own.  Most are 2d models so that they run quickly, requiring at most a
-couple of minutes to run on a desktop machine.  Each problem has an
-input script (in.*) and produces a log file (log.*) and dump file
-(dump.*) when it runs.  Some use a data file (data.*) of initial
-coordinates as additional input.  A few sample log file outputs on
-different machines and different numbers of processors are included in
-the directories to compare your answers to.  E.g. a log file like
-log.crack.foo.P means it ran on P processors of machine "foo".
-
-For examples that use input data files, many of them were produced by
-"Pizza.py"_http://pizza.sandia.gov or setup tools described in the
-"Additional Tools"_Section_tools.html section of the LAMMPS
-documentation and provided with the LAMMPS distribution.
-
-If you uncomment the "dump"_dump.html command in the input script, a
-text dump file will be produced, which can be animated by various
-"visualization programs"_http://lammps.sandia.gov/viz.html.  It can
-also be animated using the xmovie tool described in the "Additional
-Tools"_Section_tools.html section of the LAMMPS documentation.
-
-If you uncomment the "dump image"_dump.html command in the input
-script, and assuming you have built LAMMPS with a JPG library, JPG
-snapshot images will be produced when the simulation runs.  They can
-be quickly post-processed into a movie using commands described on the
-"dump image"_dump_image.html doc page.
-
-Animations of many of these examples can be viewed on the Movies
-section of the "LAMMPS WWW Site"_lws.
-
-These are the sample problems in the examples sub-directories:
-
-balance:  dynamic load balancing, 2d system
-body:     body particles, 2d system
-colloid:  big colloid particles in a small particle solvent, 2d system
-comb:	  models using the COMB potential
-crack:	  crack propagation in a 2d solid
-cuda:     use of the USER-CUDA package for GPU acceleration
-dipole:   point dipolar particles, 2d system
-dreiding: methanol via Dreiding FF
-eim:      NaCl using the EIM potential
-ellipse:  ellipsoidal particles in spherical solvent, 2d system
-flow:	  Couette and Poiseuille flow in a 2d channel
-friction: frictional contact of spherical asperities between 2d surfaces
-gpu:      use of the GPU package for GPU acceleration
-hugoniostat: Hugoniostat shock dynamics
-indent:	  spherical indenter into a 2d solid
-intel:    use of the USER-INTEL package for CPU or Intel(R) Xeon Phi(TM) coprocessor
-kim:      use of potentials in Knowledge Base for Interatomic Models (KIM)
-line:     line segment particles in 2d rigid bodies
-meam:	  MEAM test for SiC and shear (same as shear examples)
-melt:	  rapid melt of 3d LJ system
-micelle:  self-assembly of small lipid-like molecules into 2d bilayers
-min:	  energy minimization of 2d LJ melt
-msst:	  MSST shock dynamics
-nb3b:     use of nonbonded 3-body harmonic pair style
-neb:	  nudged elastic band (NEB) calculation for barrier finding
-nemd:	  non-equilibrium MD of 2d sheared system
-obstacle: flow around two voids in a 2d channel
-peptide:  dynamics of a small solvated peptide chain (5-mer)
-peri:	  Peridynamic model of cylinder impacted by indenter
-pour:     pouring of granular particles into a 3d box, then chute flow
-prd:      parallel replica dynamics of vacancy diffusion in bulk Si
-qeq:      use of the QEQ pacakge for charge equilibration
-reax:     RDX and TATB models using the ReaxFF
-rigid:    rigid bodies modeled as independent or coupled
-shear:    sideways shear applied to 2d solid, with and without a void
-snap:     NVE dynamics for BCC tantalum crystal using SNAP potential
-srd:      stochastic rotation dynamics (SRD) particles as solvent
-tad:      temperature-accelerated dynamics of vacancy diffusion in bulk Si
-tri:      triangular particles in rigid bodies :tb(s=:)
-vashishta: models using the Vashishta potential
-
-Here is how you might run and visualize one of the sample problems:
-
-cd indent
-cp ../../src/lmp_linux .           # copy LAMMPS executable to this dir
-lmp_linux -in in.indent            # run the problem :pre
-
-Running the simulation produces the files {dump.indent} and
-{log.lammps}.  You can visualize the dump file as follows:
-
-../../tools/xmovie/xmovie -scale dump.indent :pre
-
-If you uncomment the "dump image"_dump_image.html line(s) in the input
-script a series of JPG images will be produced by the run.  These can
-be viewed individually or turned into a movie or animated by tools
-like ImageMagick or QuickTime or various Windows-based tools.  See the
-"dump image"_dump_image.html doc page for more details.  E.g. this
-Imagemagick command would create a GIF file suitable for viewing in a
-browser.
-
-% convert -loop 1 *.jpg foo.gif :pre
-
-:line
-
-There is also a COUPLE directory with examples of how to use LAMMPS as
-a library, either by itself or in tandem with another code or library.
-See the COUPLE/README file to get started.
-
-There is also an ELASTIC directory with an example script for
-computing elastic constants at zero temperature, using an Si example.  See
-the ELASTIC/in.elastic file for more info.
-
-There is also an ELASTIC_T directory with an example script for
-computing elastic constants at finite temperature, using an Si example.  See
-the ELASTIC_T/in.elastic file for more info.
-
-There is also a USER directory which contains subdirectories of
-user-provided examples for user packages.  See the README files in
-those directories for more info.  See the
-"Section_start.html"_Section_start.html file for more info about user
-packages.

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-<li class="toctree-l1 current"><a class="current reference internal" href="">13. Future and history</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="#coming-attractions">13.1. Coming attractions</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#past-versions">13.2. Past versions</a></li>
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-  <div class="section" id="future-and-history">
-<h1>13. Future and history<a class="headerlink" href="#future-and-history" title="Permalink to this headline">¶</a></h1>
-<p>This section lists features we plan to add to LAMMPS, features of
-previous versions of LAMMPS, and features of other parallel molecular
-dynamics codes our group has distributed.</p>
-<div class="line-block">
-<div class="line">13.1 <a class="reference internal" href="#hist-1"><span>Coming attractions</span></a></div>
-<div class="line">13.2 <a class="reference internal" href="#hist-2"><span>Past versions</span></a></div>
-<div class="line"><br /></div>
-</div>
-<div class="section" id="coming-attractions">
-<span id="hist-1"></span><h2>13.1. Coming attractions<a class="headerlink" href="#coming-attractions" title="Permalink to this headline">¶</a></h2>
-<p>The <a class="reference external" href="http://lammps.sandia.gov/future.html">Wish list link</a> on the
-LAMMPS WWW page gives a list of features we are hoping to add to
-LAMMPS in the future, including contact names of individuals you can
-email if you are interested in contributing to the developement or
-would be a future user of that feature.</p>
-<p>You can also send <a class="reference external" href="http://lammps.sandia.gov/authors.html">email to the developers</a> if you want to add
-your wish to the list.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="past-versions">
-<span id="hist-2"></span><h2>13.2. Past versions<a class="headerlink" href="#past-versions" title="Permalink to this headline">¶</a></h2>
-<p>LAMMPS development began in the mid 1990s under a cooperative research
-&amp; development agreement (CRADA) between two DOE labs (Sandia and LLNL)
-and 3 companies (Cray, Bristol Myers Squibb, and Dupont). The goal was
-to develop a large-scale parallel classical MD code; the coding effort
-was led by Steve Plimpton at Sandia.</p>
-<p>After the CRADA ended, a final F77 version, LAMMPS 99, was
-released. As development of LAMMPS continued at Sandia, its memory
-management was converted to F90; a final F90 version was released as
-LAMMPS 2001.</p>
-<p>The current LAMMPS is a rewrite in C++ and was first publicly released
-as an open source code in 2004. It includes many new features beyond
-those in LAMMPS 99 or 2001. It also includes features from older
-parallel MD codes written at Sandia, namely ParaDyn, Warp, and
-GranFlow (see below).</p>
-<p>In late 2006 we began merging new capabilities into LAMMPS that were
-developed by Aidan Thompson at Sandia for his MD code GRASP, which has
-a parallel framework similar to LAMMPS. Most notably, these have
-included many-body potentials - Stillinger-Weber, Tersoff, ReaxFF -
-and the associated charge-equilibration routines needed for ReaxFF.</p>
-<p>The <a class="reference external" href="http://lammps.sandia.gov/history.html">History link</a> on the
-LAMMPS WWW page gives a timeline of features added to the
-C++ open-source version of LAMMPS over the last several years.</p>
-<p>These older codes are available for download from the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW site</a>, except for Warp &amp; GranFlow which were primarily used
-internally.  A brief listing of their features is given here.</p>
-<p>LAMMPS 2001</p>
-<ul class="simple">
-<li>F90 + MPI</li>
-<li>dynamic memory</li>
-<li>spatial-decomposition parallelism</li>
-<li>NVE, NVT, NPT, NPH, rRESPA integrators</li>
-<li>LJ and Coulombic pairwise force fields</li>
-<li>all-atom, united-atom, bead-spring polymer force fields</li>
-<li>CHARMM-compatible force fields</li>
-<li>class 2 force fields</li>
-<li>3d/2d Ewald &amp; PPPM</li>
-<li>various force and temperature constraints</li>
-<li>SHAKE</li>
-<li>Hessian-free truncated-Newton minimizer</li>
-<li>user-defined diagnostics</li>
-</ul>
-<p>LAMMPS 99</p>
-<ul class="simple">
-<li>F77 + MPI</li>
-<li>static memory allocation</li>
-<li>spatial-decomposition parallelism</li>
-<li>most of the LAMMPS 2001 features with a few exceptions</li>
-<li>no 2d Ewald &amp; PPPM</li>
-<li>molecular force fields are missing a few CHARMM terms</li>
-<li>no SHAKE</li>
-</ul>
-<p>Warp</p>
-<ul class="simple">
-<li>F90 + MPI</li>
-<li>spatial-decomposition parallelism</li>
-<li>embedded atom method (EAM) metal potentials + LJ</li>
-<li>lattice and grain-boundary atom creation</li>
-<li>NVE, NVT integrators</li>
-<li>boundary conditions for applying shear stresses</li>
-<li>temperature controls for actively sheared systems</li>
-<li>per-atom energy and centro-symmetry computation and output</li>
-</ul>
-<p>ParaDyn</p>
-<ul class="simple">
-<li>F77 + MPI</li>
-<li>atom- and force-decomposition parallelism</li>
-<li>embedded atom method (EAM) metal potentials</li>
-<li>lattice atom creation</li>
-<li>NVE, NVT, NPT integrators</li>
-<li>all serial DYNAMO features for controls and constraints</li>
-</ul>
-<p>GranFlow</p>
-<ul class="simple">
-<li>F90 + MPI</li>
-<li>spatial-decomposition parallelism</li>
-<li>frictional granular potentials</li>
-<li>NVE integrator</li>
-<li>boundary conditions for granular flow and packing and walls</li>
-<li>particle insertion</li>
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-<li class="toctree-l1 current"><a class="current reference internal" href="">1. Introduction</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="#what-is-lammps">1.1. What is LAMMPS</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#lammps-features">1.2. LAMMPS features</a><ul>
-<li class="toctree-l3"><a class="reference internal" href="#general-features">1.2.1. General features</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#particle-and-model-types">1.2.2. Particle and model types</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#force-fields">1.2.3. Force fields</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#atom-creation">1.2.4. Atom creation</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#ensembles-constraints-and-boundary-conditions">1.2.5. Ensembles, constraints, and boundary conditions</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#integrators">1.2.6. Integrators</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#diagnostics">1.2.7. Diagnostics</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#output">1.2.8. Output</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#multi-replica-models">1.2.9. Multi-replica models</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#pre-and-post-processing">1.2.10. Pre- and post-processing</a></li>
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-</ul>
-</li>
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-<li class="toctree-l2"><a class="reference internal" href="#acknowledgments-and-citations">1.5. Acknowledgments and citations</a></li>
-</ul>
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-  <div class="section" id="introduction">
-<h1>1. Introduction<a class="headerlink" href="#introduction" title="Permalink to this headline">¶</a></h1>
-<p>This section provides an overview of what LAMMPS can and can&#8217;t do,
-describes what it means for LAMMPS to be an open-source code, and
-acknowledges the funding and people who have contributed to LAMMPS
-over the years.</p>
-<div class="line-block">
-<div class="line">1.1 <a class="reference internal" href="#intro-1"><span>What is LAMMPS</span></a></div>
-<div class="line">1.2 <a class="reference internal" href="#intro-2"><span>LAMMPS features</span></a></div>
-<div class="line">1.3 <a class="reference internal" href="#intro-3"><span>LAMMPS non-features</span></a></div>
-<div class="line">1.4 <a class="reference internal" href="#intro-4"><span>Open source distribution</span></a></div>
-<div class="line">1.5 <a class="reference internal" href="#intro-5"><span>Acknowledgments and citations</span></a></div>
-<div class="line"><br /></div>
-</div>
-<div class="section" id="what-is-lammps">
-<span id="intro-1"></span><h2>1.1. What is LAMMPS<a class="headerlink" href="#what-is-lammps" title="Permalink to this headline">¶</a></h2>
-<p>LAMMPS is a classical molecular dynamics code that models an ensemble
-of particles in a liquid, solid, or gaseous state.  It can model
-atomic, polymeric, biological, metallic, granular, and coarse-grained
-systems using a variety of force fields and boundary conditions.</p>
-<p>For examples of LAMMPS simulations, see the Publications page of the
-<a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>.</p>
-<p>LAMMPS runs efficiently on single-processor desktop or laptop
-machines, but is designed for parallel computers.  It will run on any
-parallel machine that compiles C++ and supports the <a class="reference external" href="http://www-unix.mcs.anl.gov/mpi">MPI</a>
-message-passing library.  This includes distributed- or shared-memory
-parallel machines and Beowulf-style clusters.</p>
-<p>LAMMPS can model systems with only a few particles up to millions or
-billions.  See <a class="reference internal" href="Section_perf.html"><em>Section_perf</em></a> for information on
-LAMMPS performance and scalability, or the Benchmarks section of the
-<a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>.</p>
-<p>LAMMPS is a freely-available open-source code, distributed under the
-terms of the <a class="reference external" href="http://www.gnu.org/copyleft/gpl.html">GNU Public License</a>, which means you can use or
-modify the code however you wish.  See <a class="reference internal" href="#intro-4"><span>this section</span></a> for a
-brief discussion of the open-source philosophy.</p>
-<p>LAMMPS is designed to be easy to modify or extend with new
-capabilities, such as new force fields, atom types, boundary
-conditions, or diagnostics.  See <a class="reference internal" href="Section_modify.html"><em>Section_modify</em></a>
-for more details.</p>
-<p>The current version of LAMMPS is written in C++.  Earlier versions
-were written in F77 and F90.  See
-<a class="reference internal" href="Section_history.html"><em>Section_history</em></a> for more information on
-different versions.  All versions can be downloaded from the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>.</p>
-<p>LAMMPS was originally developed under a US Department of Energy CRADA
-(Cooperative Research and Development Agreement) between two DOE labs
-and 3 companies.  It is distributed by <a class="reference external" href="http://www.sandia.gov">Sandia National Labs</a>.
-See <a class="reference internal" href="#intro-5"><span>this section</span></a> for more information on LAMMPS funding and
-individuals who have contributed to LAMMPS.</p>
-<p>In the most general sense, LAMMPS integrates Newton&#8217;s equations of
-motion for collections of atoms, molecules, or macroscopic particles
-that interact via short- or long-range forces with a variety of
-initial and/or boundary conditions.  For computational efficiency
-LAMMPS uses neighbor lists to keep track of nearby particles.  The
-lists are optimized for systems with particles that are repulsive at
-short distances, so that the local density of particles never becomes
-too large.  On parallel machines, LAMMPS uses spatial-decomposition
-techniques to partition the simulation domain into small 3d
-sub-domains, one of which is assigned to each processor.  Processors
-communicate and store &#8220;ghost&#8221; atom information for atoms that border
-their sub-domain.  LAMMPS is most efficient (in a parallel sense) for
-systems whose particles fill a 3d rectangular box with roughly uniform
-density.  Papers with technical details of the algorithms used in
-LAMMPS are listed in <a class="reference internal" href="#intro-5"><span>this section</span></a>.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="lammps-features">
-<span id="intro-2"></span><h2>1.2. LAMMPS features<a class="headerlink" href="#lammps-features" title="Permalink to this headline">¶</a></h2>
-<p>This section highlights LAMMPS features, with pointers to specific
-commands which give more details.  If LAMMPS doesn&#8217;t have your
-favorite interatomic potential, boundary condition, or atom type, see
-<a class="reference internal" href="Section_modify.html"><em>Section_modify</em></a>, which describes how you can add
-it to LAMMPS.</p>
-<div class="section" id="general-features">
-<h3>1.2.1. General features<a class="headerlink" href="#general-features" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li>runs on a single processor or in parallel</li>
-<li>distributed-memory message-passing parallelism (MPI)</li>
-<li>spatial-decomposition of simulation domain for parallelism</li>
-<li>open-source distribution</li>
-<li>highly portable C++</li>
-<li>optional libraries used: MPI and single-processor FFT</li>
-<li>GPU (CUDA and OpenCL), Intel(R) Xeon Phi(TM) coprocessors, and OpenMP support for many code features</li>
-<li>easy to extend with new features and functionality</li>
-<li>runs from an input script</li>
-<li>syntax for defining and using variables and formulas</li>
-<li>syntax for looping over runs and breaking out of loops</li>
-<li>run one or multiple simulations simultaneously (in parallel) from one script</li>
-<li>build as library, invoke LAMMPS thru library interface or provided Python wrapper</li>
-<li>couple with other codes: LAMMPS calls other code, other code calls LAMMPS, umbrella code calls both</li>
-</ul>
-</div>
-<div class="section" id="particle-and-model-types">
-<h3>1.2.2. Particle and model types<a class="headerlink" href="#particle-and-model-types" title="Permalink to this headline">¶</a></h3>
-<p>(<a class="reference internal" href="atom_style.html"><em>atom style</em></a> command)</p>
-<ul class="simple">
-<li>atoms</li>
-<li>coarse-grained particles (e.g. bead-spring polymers)</li>
-<li>united-atom polymers or organic molecules</li>
-<li>all-atom polymers, organic molecules, proteins, DNA</li>
-<li>metals</li>
-<li>granular materials</li>
-<li>coarse-grained mesoscale models</li>
-<li>finite-size spherical and ellipsoidal particles</li>
-<li>finite-size  line segment (2d) and triangle (3d) particles</li>
-<li>point dipole particles</li>
-<li>rigid collections of particles</li>
-<li>hybrid combinations of these</li>
-</ul>
-</div>
-<div class="section" id="force-fields">
-<h3>1.2.3. Force fields<a class="headerlink" href="#force-fields" title="Permalink to this headline">¶</a></h3>
-<p>(<a class="reference internal" href="pair_style.html"><em>pair style</em></a>, <a class="reference internal" href="bond_style.html"><em>bond style</em></a>,
-<a class="reference internal" href="angle_style.html"><em>angle style</em></a>, <a class="reference internal" href="dihedral_style.html"><em>dihedral style</em></a>,
-<a class="reference internal" href="improper_style.html"><em>improper style</em></a>, <a class="reference internal" href="kspace_style.html"><em>kspace style</em></a>
-commands)</p>
-<ul class="simple">
-<li>pairwise potentials: Lennard-Jones, Buckingham, Morse, Born-Mayer-Huggins,     Yukawa, soft, class 2 (COMPASS), hydrogen bond, tabulated</li>
-<li>charged pairwise potentials: Coulombic, point-dipole</li>
-<li>manybody potentials: EAM, Finnis/Sinclair EAM, modified EAM (MEAM),     embedded ion method (EIM), EDIP, ADP, Stillinger-Weber, Tersoff,     REBO, AIREBO, ReaxFF, COMB, SNAP, Streitz-Mintmire, 3-body polymorphic</li>
-<li>long-range interactions for charge, point-dipoles, and LJ dispersion:     Ewald, Wolf, PPPM (similar to particle-mesh Ewald)</li>
-<li>polarization models: <a class="reference internal" href="fix_qeq.html"><em>QEq</em></a>,     <a class="reference internal" href="Section_howto.html#howto-26"><span>core/shell model</span></a>,     <a class="reference internal" href="Section_howto.html#howto-27"><span>Drude dipole model</span></a></li>
-<li>charge equilibration (QEq via dynamic, point, shielded, Slater methods)</li>
-<li>coarse-grained potentials: DPD, GayBerne, REsquared, colloidal, DLVO</li>
-<li>mesoscopic potentials: granular, Peridynamics, SPH</li>
-<li>electron force field (eFF, AWPMD)</li>
-<li>bond potentials: harmonic, FENE, Morse, nonlinear, class 2,     quartic (breakable)</li>
-<li>angle potentials: harmonic, CHARMM, cosine, cosine/squared, cosine/periodic,     class 2 (COMPASS)</li>
-<li>dihedral potentials: harmonic, CHARMM, multi-harmonic, helix,     class 2 (COMPASS), OPLS</li>
-<li>improper potentials: harmonic, cvff, umbrella, class 2 (COMPASS)</li>
-<li>polymer potentials: all-atom, united-atom, bead-spring, breakable</li>
-<li>water potentials: TIP3P, TIP4P, SPC</li>
-<li>implicit solvent potentials: hydrodynamic lubrication, Debye</li>
-<li>force-field compatibility with common CHARMM, AMBER, DREIDING,     OPLS, GROMACS, COMPASS options</li>
-<li>access to <a class="reference external" href="http://openkim.org">KIM archive</a> of potentials via     <a class="reference internal" href="pair_kim.html"><em>pair kim</em></a></li>
-<li>hybrid potentials: multiple pair, bond, angle, dihedral, improper     potentials can be used in one simulation</li>
-<li>overlaid potentials: superposition of multiple pair potentials</li>
-</ul>
-</div>
-<div class="section" id="atom-creation">
-<h3>1.2.4. Atom creation<a class="headerlink" href="#atom-creation" title="Permalink to this headline">¶</a></h3>
-<p>(<a class="reference internal" href="read_data.html"><em>read_data</em></a>, <a class="reference internal" href="lattice.html"><em>lattice</em></a>,
-<a class="reference internal" href="create_atoms.html"><em>create_atoms</em></a>, <a class="reference internal" href="delete_atoms.html"><em>delete_atoms</em></a>,
-<a class="reference internal" href="displace_atoms.html"><em>displace_atoms</em></a>, <a class="reference internal" href="replicate.html"><em>replicate</em></a> commands)</p>
-<ul class="simple">
-<li>read in atom coords from files</li>
-<li>create atoms on one or more lattices (e.g. grain boundaries)</li>
-<li>delete geometric or logical groups of atoms (e.g. voids)</li>
-<li>replicate existing atoms multiple times</li>
-<li>displace atoms</li>
-</ul>
-</div>
-<div class="section" id="ensembles-constraints-and-boundary-conditions">
-<h3>1.2.5. Ensembles, constraints, and boundary conditions<a class="headerlink" href="#ensembles-constraints-and-boundary-conditions" title="Permalink to this headline">¶</a></h3>
-<p>(<a class="reference internal" href="fix.html"><em>fix</em></a> command)</p>
-<ul class="simple">
-<li>2d or 3d systems</li>
-<li>orthogonal or non-orthogonal (triclinic symmetry) simulation domains</li>
-<li>constant NVE, NVT, NPT, NPH, Parinello/Rahman integrators</li>
-<li>thermostatting options for groups and geometric regions of atoms</li>
-<li>pressure control via Nose/Hoover or Berendsen barostatting in 1 to 3 dimensions</li>
-<li>simulation box deformation (tensile and shear)</li>
-<li>harmonic (umbrella) constraint forces</li>
-<li>rigid body constraints</li>
-<li>SHAKE bond and angle constraints</li>
-<li>Monte Carlo bond breaking, formation, swapping</li>
-<li>atom/molecule insertion and deletion</li>
-<li>walls of various kinds</li>
-<li>non-equilibrium molecular dynamics (NEMD)</li>
-<li>variety of additional boundary conditions and constraints</li>
-</ul>
-</div>
-<div class="section" id="integrators">
-<h3>1.2.6. Integrators<a class="headerlink" href="#integrators" title="Permalink to this headline">¶</a></h3>
-<p>(<a class="reference internal" href="run.html"><em>run</em></a>, <a class="reference internal" href="run_style.html"><em>run_style</em></a>, <a class="reference internal" href="minimize.html"><em>minimize</em></a> commands)</p>
-<ul class="simple">
-<li>velocity-Verlet integrator</li>
-<li>Brownian dynamics</li>
-<li>rigid body integration</li>
-<li>energy minimization via conjugate gradient or steepest descent relaxation</li>
-<li>rRESPA hierarchical timestepping</li>
-<li>rerun command for post-processing of dump files</li>
-</ul>
-</div>
-<div class="section" id="diagnostics">
-<h3>1.2.7. Diagnostics<a class="headerlink" href="#diagnostics" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li>see the various flavors of the <a class="reference internal" href="fix.html"><em>fix</em></a> and <a class="reference internal" href="compute.html"><em>compute</em></a> commands</li>
-</ul>
-</div>
-<div class="section" id="output">
-<h3>1.2.8. Output<a class="headerlink" href="#output" title="Permalink to this headline">¶</a></h3>
-<p>(<a class="reference internal" href="dump.html"><em>dump</em></a>, <a class="reference internal" href="restart.html"><em>restart</em></a> commands)</p>
-<ul class="simple">
-<li>log file of thermodynamic info</li>
-<li>text dump files of atom coords, velocities, other per-atom quantities</li>
-<li>binary restart files</li>
-<li>parallel I/O of dump and restart files</li>
-<li>per-atom quantities (energy, stress, centro-symmetry parameter, CNA, etc)</li>
-<li>user-defined system-wide (log file) or per-atom (dump file) calculations</li>
-<li>spatial and time averaging of per-atom quantities</li>
-<li>time averaging of system-wide quantities</li>
-<li>atom snapshots in native, XYZ, XTC, DCD, CFG formats</li>
-</ul>
-</div>
-<div class="section" id="multi-replica-models">
-<h3>1.2.9. Multi-replica models<a class="headerlink" href="#multi-replica-models" title="Permalink to this headline">¶</a></h3>
-<p><a class="reference internal" href="neb.html"><em>nudged elastic band</em></a>
-<a class="reference internal" href="prd.html"><em>parallel replica dynamics</em></a>
-<a class="reference internal" href="tad.html"><em>temperature accelerated dynamics</em></a>
-<a class="reference internal" href="temper.html"><em>parallel tempering</em></a></p>
-</div>
-<div class="section" id="pre-and-post-processing">
-<h3>1.2.10. Pre- and post-processing<a class="headerlink" href="#pre-and-post-processing" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li>Various pre- and post-processing serial tools are packaged
-with LAMMPS; see these <a class="reference internal" href="Section_tools.html"><em>doc pages</em></a>.</li>
-<li>Our group has also written and released a separate toolkit called
-<a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">Pizza.py</a> which provides tools for doing setup, analysis,
-plotting, and visualization for LAMMPS simulations.  Pizza.py is
-written in <a class="reference external" href="http://www.python.org">Python</a> and is available for download from <a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">the Pizza.py WWW site</a>.</li>
-</ul>
-</div>
-<div class="section" id="specialized-features">
-<h3>1.2.11. Specialized features<a class="headerlink" href="#specialized-features" title="Permalink to this headline">¶</a></h3>
-<p>These are LAMMPS capabilities which you may not think of as typical
-molecular dynamics options:</p>
-<ul class="simple">
-<li><a class="reference internal" href="balance.html"><em>static</em></a> and <a class="reference internal" href="fix_balance.html"><em>dynamic load-balancing</em></a></li>
-<li><a class="reference internal" href="body.html"><em>generalized aspherical particles</em></a></li>
-<li><a class="reference internal" href="fix_srd.html"><em>stochastic rotation dynamics (SRD)</em></a></li>
-<li><a class="reference internal" href="fix_imd.html"><em>real-time visualization and interactive MD</em></a></li>
-<li>calculate <a class="reference internal" href="compute_xrd.html"><em>virtual diffraction patterns</em></a></li>
-<li><a class="reference internal" href="fix_atc.html"><em>atom-to-continuum coupling</em></a> with finite elements</li>
-<li>coupled rigid body integration via the <a class="reference internal" href="fix_poems.html"><em>POEMS</em></a> library</li>
-<li><a class="reference internal" href="fix_qmmm.html"><em>QM/MM coupling</em></a></li>
-<li><a class="reference internal" href="fix_ipi.html"><em>path-integral molecular dynamics (PIMD)</em></a> and <a class="reference internal" href="fix_pimd.html"><em>this as well</em></a></li>
-<li>Monte Carlo via <a class="reference internal" href="fix_gcmc.html"><em>GCMC</em></a> and <a class="reference internal" href="fix_tfmc.html"><em>tfMC</em></a> and <code class="xref doc docutils literal"><span class="pre">atom</span> <span class="pre">swapping</span></code></li>
-<li><a class="reference internal" href="pair_dsmc.html"><em>Direct Simulation Monte Carlo</em></a> for low-density fluids</li>
-<li><a class="reference internal" href="pair_peri.html"><em>Peridynamics mesoscale modeling</em></a></li>
-<li><a class="reference internal" href="fix_lb_fluid.html"><em>Lattice Boltzmann fluid</em></a></li>
-<li><a class="reference internal" href="fix_tmd.html"><em>targeted</em></a> and <a class="reference internal" href="fix_smd.html"><em>steered</em></a> molecular dynamics</li>
-<li><a class="reference internal" href="fix_ttm.html"><em>two-temperature electron model</em></a></li>
-</ul>
-<hr class="docutils" />
-</div>
-</div>
-<div class="section" id="lammps-non-features">
-<span id="intro-3"></span><h2>1.3. LAMMPS non-features<a class="headerlink" href="#lammps-non-features" title="Permalink to this headline">¶</a></h2>
-<p>LAMMPS is designed to efficiently compute Newton&#8217;s equations of motion
-for a system of interacting particles.  Many of the tools needed to
-pre- and post-process the data for such simulations are not included
-in the LAMMPS kernel for several reasons:</p>
-<ul class="simple">
-<li>the desire to keep LAMMPS simple</li>
-<li>they are not parallel operations</li>
-<li>other codes already do them</li>
-<li>limited development resources</li>
-</ul>
-<p>Specifically, LAMMPS itself does not:</p>
-<ul class="simple">
-<li>run thru a GUI</li>
-<li>build molecular systems</li>
-<li>assign force-field coefficients automagically</li>
-<li>perform sophisticated analyses of your MD simulation</li>
-<li>visualize your MD simulation</li>
-<li>plot your output data</li>
-</ul>
-<p>A few tools for pre- and post-processing tasks are provided as part of
-the LAMMPS package; they are described in <a class="reference internal" href="Section_tools.html"><em>this section</em></a>.  However, many people use other codes or
-write their own tools for these tasks.</p>
-<p>As noted above, our group has also written and released a separate
-toolkit called <a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">Pizza.py</a> which addresses some of the listed
-bullets.  It provides tools for doing setup, analysis, plotting, and
-visualization for LAMMPS simulations.  Pizza.py is written in
-<a class="reference external" href="http://www.python.org">Python</a> and is available for download from <a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">the Pizza.py WWW site</a>.</p>
-<p>LAMMPS requires as input a list of initial atom coordinates and types,
-molecular topology information, and force-field coefficients assigned
-to all atoms and bonds.  LAMMPS will not build molecular systems and
-assign force-field parameters for you.</p>
-<p>For atomic systems LAMMPS provides a <a class="reference internal" href="create_atoms.html"><em>create_atoms</em></a>
-command which places atoms on solid-state lattices (fcc, bcc,
-user-defined, etc).  Assigning small numbers of force field
-coefficients can be done via the <a class="reference internal" href="pair_coeff.html"><em>pair coeff</em></a>, <a class="reference internal" href="bond_coeff.html"><em>bond coeff</em></a>, <a class="reference internal" href="angle_coeff.html"><em>angle coeff</em></a>, etc commands.
-For molecular systems or more complicated simulation geometries, users
-typically use another code as a builder and convert its output to
-LAMMPS input format, or write their own code to generate atom
-coordinate and molecular topology for LAMMPS to read in.</p>
-<p>For complicated molecular systems (e.g. a protein), a multitude of
-topology information and hundreds of force-field coefficients must
-typically be specified.  We suggest you use a program like
-<a class="reference external" href="http://www.scripps.edu/brooks">CHARMM</a> or <a class="reference external" href="http://amber.scripps.edu">AMBER</a> or other molecular builders to setup
-such problems and dump its information to a file.  You can then
-reformat the file as LAMMPS input.  Some of the tools in <a class="reference internal" href="Section_tools.html"><em>this section</em></a> can assist in this process.</p>
-<p>Similarly, LAMMPS creates output files in a simple format.  Most users
-post-process these files with their own analysis tools or re-format
-them for input into other programs, including visualization packages.
-If you are convinced you need to compute something on-the-fly as
-LAMMPS runs, see <a class="reference internal" href="Section_modify.html"><em>Section_modify</em></a> for a discussion
-of how you can use the <a class="reference internal" href="dump.html"><em>dump</em></a> and <a class="reference internal" href="compute.html"><em>compute</em></a> and
-<a class="reference internal" href="fix.html"><em>fix</em></a> commands to print out data of your choosing.  Keep in
-mind that complicated computations can slow down the molecular
-dynamics timestepping, particularly if the computations are not
-parallel, so it is often better to leave such analysis to
-post-processing codes.</p>
-<p>A very simple (yet fast) visualizer is provided with the LAMMPS
-package - see the <a class="reference internal" href="Section_tools.html#xmovie"><span>xmovie</span></a> tool in <a class="reference internal" href="Section_tools.html"><em>this section</em></a>.  It creates xyz projection views of
-atomic coordinates and animates them.  We find it very useful for
-debugging purposes.  For high-quality visualization we recommend the
-following packages:</p>
-<ul class="simple">
-<li><a class="reference external" href="http://www.ks.uiuc.edu/Research/vmd">VMD</a></li>
-<li><a class="reference external" href="http://mt.seas.upenn.edu/Archive/Graphics/A">AtomEye</a></li>
-<li><a class="reference external" href="http://pymol.sourceforge.net">PyMol</a></li>
-<li><a class="reference external" href="http://www.bmsc.washington.edu/raster3d/raster3d.html">Raster3d</a></li>
-<li><a class="reference external" href="http://www.openrasmol.org">RasMol</a></li>
-</ul>
-<p>Other features that LAMMPS does not yet (and may never) support are
-discussed in <a class="reference internal" href="Section_history.html"><em>Section_history</em></a>.</p>
-<p>Finally, these are freely-available molecular dynamics codes, most of
-them parallel, which may be well-suited to the problems you want to
-model.  They can also be used in conjunction with LAMMPS to perform
-complementary modeling tasks.</p>
-<ul class="simple">
-<li><a class="reference external" href="http://www.scripps.edu/brooks">CHARMM</a></li>
-<li><a class="reference external" href="http://amber.scripps.edu">AMBER</a></li>
-<li><a class="reference external" href="http://www.ks.uiuc.edu/Research/namd/">NAMD</a></li>
-<li><a class="reference external" href="http://www.emsl.pnl.gov/docs/nwchem/nwchem.html">NWCHEM</a></li>
-<li><a class="reference external" href="http://www.cse.clrc.ac.uk/msi/software/DL_POLY">DL_POLY</a></li>
-<li><a class="reference external" href="http://dasher.wustl.edu/tinker">Tinker</a></li>
-</ul>
-<p>CHARMM, AMBER, NAMD, NWCHEM, and Tinker are designed primarily for
-modeling biological molecules.  CHARMM and AMBER use
-atom-decomposition (replicated-data) strategies for parallelism; NAMD
-and NWCHEM use spatial-decomposition approaches, similar to LAMMPS.
-Tinker is a serial code.  DL_POLY includes potentials for a variety of
-biological and non-biological materials; both a replicated-data and
-spatial-decomposition version exist.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="open-source-distribution">
-<span id="intro-4"></span><h2>1.4. Open source distribution<a class="headerlink" href="#open-source-distribution" title="Permalink to this headline">¶</a></h2>
-<p>LAMMPS comes with no warranty of any kind.  As each source file states
-in its header, it is a copyrighted code that is distributed free-of-
-charge, under the terms of the <a class="reference external" href="http://www.gnu.org/copyleft/gpl.html">GNU Public License</a> (GPL).  This
-is often referred to as open-source distribution - see
-<a class="reference external" href="http://www.gnu.org">www.gnu.org</a> or <a class="reference external" href="http://www.opensource.org">www.opensource.org</a> for more
-details.  The legal text of the GPL is in the LICENSE file that is
-included in the LAMMPS distribution.</p>
-<p>Here is a summary of what the GPL means for LAMMPS users:</p>
-<p>(1) Anyone is free to use, modify, or extend LAMMPS in any way they
-choose, including for commercial purposes.</p>
-<p>(2) If you distribute a modified version of LAMMPS, it must remain
-open-source, meaning you distribute it under the terms of the GPL.
-You should clearly annotate such a code as a derivative version of
-LAMMPS.</p>
-<p>(3) If you release any code that includes LAMMPS source code, then it
-must also be open-sourced, meaning you distribute it under the terms
-of the GPL.</p>
-<p>(4) If you give LAMMPS files to someone else, the GPL LICENSE file and
-source file headers (including the copyright and GPL notices) should
-remain part of the code.</p>
-<p>In the spirit of an open-source code, these are various ways you can
-contribute to making LAMMPS better.  You can send email to the
-<a class="reference external" href="http://lammps.sandia.gov/authors.html">developers</a> on any of these
-items.</p>
-<ul class="simple">
-<li>Point prospective users to the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>.  Mention it in
-talks or link to it from your WWW site.</li>
-<li>If you find an error or omission in this manual or on the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>, or have a suggestion for something to clarify or include,
-send an email to the
-<a class="reference external" href="http://lammps.sandia.gov/authors.html">developers</a>.</li>
-<li>If you find a bug, <a class="reference internal" href="Section_errors.html#err-2"><span>Section_errors 2</span></a>
-describes how to report it.</li>
-<li>If you publish a paper using LAMMPS results, send the citation (and
-any cool pictures or movies if you like) to add to the Publications,
-Pictures, and Movies pages of the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>, with links
-and attributions back to you.</li>
-<li>Create a new Makefile.machine that can be added to the src/MAKE
-directory.</li>
-<li>The tools sub-directory of the LAMMPS distribution has various
-stand-alone codes for pre- and post-processing of LAMMPS data.  More
-details are given in <a class="reference internal" href="Section_tools.html"><em>Section_tools</em></a>.  If you write
-a new tool that users will find useful, it can be added to the LAMMPS
-distribution.</li>
-<li>LAMMPS is designed to be easy to extend with new code for features
-like potentials, boundary conditions, diagnostic computations, etc.
-<a class="reference internal" href="Section_modify.html"><em>This section</em></a> gives details.  If you add a
-feature of general interest, it can be added to the LAMMPS
-distribution.</li>
-<li>The Benchmark page of the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a> lists LAMMPS
-performance on various platforms.  The files needed to run the
-benchmarks are part of the LAMMPS distribution.  If your machine is
-sufficiently different from those listed, your timing data can be
-added to the page.</li>
-<li>You can send feedback for the User Comments page of the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>.  It might be added to the page.  No promises.</li>
-<li>Cash.  Small denominations, unmarked bills preferred.  Paper sack OK.
-Leave on desk.  VISA also accepted.  Chocolate chip cookies
-encouraged.</li>
-</ul>
-<hr class="docutils" />
-</div>
-<div class="section" id="acknowledgments-and-citations">
-<span id="intro-5"></span><h2>1.5. Acknowledgments and citations<a class="headerlink" href="#acknowledgments-and-citations" title="Permalink to this headline">¶</a></h2>
-<p>LAMMPS development has been funded by the <a class="reference external" href="http://www.doe.gov">US Department of Energy</a> (DOE), through its CRADA, LDRD, ASCI, and Genomes-to-Life
-programs and its <a class="reference external" href="http://www.sc.doe.gov/ascr/home.html">OASCR</a> and <a class="reference external" href="http://www.er.doe.gov/production/ober/ober_top.html">OBER</a> offices.</p>
-<p>Specifically, work on the latest version was funded in part by the US
-Department of Energy&#8217;s Genomics:GTL program
-(<a class="reference external" href="http://www.doegenomestolife.org">www.doegenomestolife.org</a>) under the <a class="reference external" href="http://www.genomes2life.org">project</a>, &#8220;Carbon
-Sequestration in Synechococcus Sp.: From Molecular Machines to
-Hierarchical Modeling&#8221;.</p>
-<p>The following paper describe the basic parallel algorithms used in
-LAMMPS.  If you use LAMMPS results in your published work, please cite
-this paper and include a pointer to the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a>
-(<a class="reference external" href="http://lammps.sandia.gov">http://lammps.sandia.gov</a>):</p>
-<p>S. J. Plimpton, <strong>Fast Parallel Algorithms for Short-Range Molecular
-Dynamics</strong>, J Comp Phys, 117, 1-19 (1995).</p>
-<p>Other papers describing specific algorithms used in LAMMPS are listed
-under the <a class="reference external" href="http://lammps.sandia.gov/cite.html">Citing LAMMPS link</a> of
-the LAMMPS WWW page.</p>
-<p>The <a class="reference external" href="http://lammps.sandia.gov/papers.html">Publications link</a> on the
-LAMMPS WWW page lists papers that have cited LAMMPS.  If your paper is
-not listed there for some reason, feel free to send us the info.  If
-the simulations in your paper produced cool pictures or animations,
-we&#8217;ll be pleased to add them to the
-<a class="reference external" href="http://lammps.sandia.gov/pictures.html">Pictures</a> or
-<a class="reference external" href="http://lammps.sandia.gov/movies.html">Movies</a> pages of the LAMMPS WWW
-site.</p>
-<p>The core group of LAMMPS developers is at Sandia National Labs:</p>
-<ul class="simple">
-<li>Steve Plimpton, sjplimp at sandia.gov</li>
-<li>Aidan Thompson, athomps at sandia.gov</li>
-<li>Paul Crozier, pscrozi at sandia.gov</li>
-</ul>
-<p>The following folks are responsible for significant contributions to
-the code, or other aspects of the LAMMPS development effort.  Many of
-the packages they have written are somewhat unique to LAMMPS and the
-code would not be as general-purpose as it is without their expertise
-and efforts.</p>
-<ul class="simple">
-<li>Axel Kohlmeyer (Temple U), akohlmey at gmail.com, SVN and Git repositories, indefatigable mail list responder, USER-CG-CMM and USER-OMP packages</li>
-<li>Roy Pollock (LLNL), Ewald and PPPM solvers</li>
-<li>Mike Brown (ORNL), brownw at ornl.gov, GPU package</li>
-<li>Greg Wagner (Sandia), gjwagne at sandia.gov, MEAM package for MEAM potential</li>
-<li>Mike Parks (Sandia), mlparks at sandia.gov, PERI package for Peridynamics</li>
-<li>Rudra Mukherjee (JPL), Rudranarayan.M.Mukherjee at jpl.nasa.gov, POEMS package for articulated rigid body motion</li>
-<li>Reese Jones (Sandia) and collaborators, rjones at sandia.gov, USER-ATC package for atom/continuum coupling</li>
-<li>Ilya Valuev (JIHT), valuev at physik.hu-berlin.de, USER-AWPMD package for wave-packet MD</li>
-<li>Christian Trott (U Tech Ilmenau), christian.trott at tu-ilmenau.de, USER-CUDA package</li>
-<li>Andres Jaramillo-Botero (Caltech), ajaramil at wag.caltech.edu, USER-EFF package for electron force field</li>
-<li>Christoph Kloss (JKU), Christoph.Kloss at jku.at, USER-LIGGGHTS package for granular models and granular/fluid coupling</li>
-<li>Metin Aktulga (LBL), hmaktulga at lbl.gov, USER-REAXC package for C version of ReaxFF</li>
-<li>Georg Gunzenmuller (EMI), georg.ganzenmueller at emi.fhg.de, USER-SPH package</li>
-</ul>
-<p>As discussed in <a class="reference internal" href="Section_history.html"><em>Section_history</em></a>, LAMMPS
-originated as a cooperative project between DOE labs and industrial
-partners. Folks involved in the design and testing of the original
-version of LAMMPS were the following:</p>
-<ul class="simple">
-<li>John Carpenter (Mayo Clinic, formerly at Cray Research)</li>
-<li>Terry Stouch (Lexicon Pharmaceuticals, formerly at Bristol Myers Squibb)</li>
-<li>Steve Lustig (Dupont)</li>
-<li>Jim Belak (LLNL)</li>
-</ul>
-</div>
-</div>
-
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doc/Section_packages.txt

@@ -1,858 +0,0 @@
-"Previous Section"_Section_commands.html - "LAMMPS WWW Site"_lws -
-"LAMMPS Documentation"_ld - "LAMMPS Commands"_lc - "Next
-Section"_Section_accelerate.html :c
-
-:link(lws,http://lammps.sandia.gov)
-:link(ld,Manual.html)
-:link(lc,Section_commands.html#comm)
-
-:line
-
-4. Packages :h3
-
-This section gives a quick overview of the add-on packages that extend
-LAMMPS functionality.
-
-4.1 "Standard packages"_#pkg_1
-4.2 "User packages"_#pkg_2 :all(b)
-
-LAMMPS includes many optional packages, which are groups of files that
-enable a specific set of features.  For example, force fields for
-molecular systems or granular systems are in packages.  You can see
-the list of all packages by typing "make package" from within the src
-directory of the LAMMPS distribution.
-
-See "Section_start 3"_Section_start.html#start_3 of the manual for
-details on how to include/exclude specific packages as part of the
-LAMMPS build process, and for more details about the differences
-between standard packages and user packages.
-
-Unless otherwise noted below, every package is independent of all the
-others.  I.e. any package can be included or excluded in a LAMMPS
-build, independent of all other packages.  However, note that some
-packages include commands derived from commands in other packages.  If
-the other package is not installed, the derived command from the new
-package will also not be installed when you include the new one.
-E.g. the pair lj/cut/coul/long/omp command from the USER-OMP package
-will not be installed as part of the USER-OMP package if the KSPACE
-package is not also installed, since it contains the pair
-lj/cut/coul/long command.  If you later install the KSPACE pacakge and
-the USER-OMP package is already installed, both the pair
-lj/cut/coul/long and lj/cut/coul/long/omp commands will be installed.
-
-The two tables below list currently available packages in LAMMPS, with
-a one-line descriptions of each.  The sections below give a few more
-details, including instructions for building LAMMPS with the package,
-either via the make command or the Make.py tool described in "Section
-2.4"_Section_start.html#start_4.
-
-:line
-:line
-
-4.1 Standard packages :h4,link(pkg_1)
-
-The current list of standard packages is as follows. 
-
-Package, Description, Author(s), Doc page, Example, Library
-ASPHERE, aspherical particles, -, "Section_howto 6.14"_Section_howto.html#howto_14, ellipse, -
-BODY, body-style particles, -, "body"_body.html, body, -
-CLASS2, class 2 force fields, -, "pair_style lj/class2"_pair_class2.html, -, -
-COLLOID, colloidal particles, -, "atom_style colloid"_atom_style.html, colloid, -
-COMPRESS, I/O compression, Axel Kohlmeyer (Temple U), "dump */gz"_dump.html, -, -
-CORESHELL, adiabatic core/shell model, Hendrik Heenen (Technical U of Munich), "Section_howto 6.25"_Section_howto.html#howto_25, coreshell, -
-DIPOLE, point dipole particles, -, "pair_style dipole/cut"_pair_dipole.html, dipole, -
-FLD, Fast Lubrication Dynamics, Kumar & Bybee & Higdon (1), "pair_style lubricateU"_pair_lubricateU.html, -, -
-GPU, GPU-enabled styles, Mike Brown (ORNL), "Section accelerate"_accelerate_gpu.html, gpu, lib/gpu
-GRANULAR, granular systems, -, "Section_howto 6.6"_Section_howto.html#howto_6, pour, -
-KIM, openKIM potentials, Smirichinski & Elliot & Tadmor (3), "pair_style kim"_pair_kim.html, kim, KIM
-KOKKOS, Kokkos-enabled styles, Trott & Edwards (4), "Section_accelerate"_accelerate_kokkos.html, kokkos, lib/kokkos
-KSPACE, long-range Coulombic solvers, -, "kspace_style"_kspace_style.html, peptide, -
-MANYBODY, many-body potentials, -, "pair_style tersoff"_pair_tersoff.html, shear, -
-MEAM, modified EAM potential, Greg Wagner (Sandia), "pair_style meam"_pair_meam.html, meam, lib/meam
-MC, Monte Carlo options, -, "fix gcmc"_fix_gcmc.html, -, -
-MOLECULE, molecular system force fields, -, "Section_howto 6.3"_Section_howto.html#howto_3, peptide, -
-OPT, optimized pair styles, Fischer & Richie & Natoli (2), "Section accelerate"_accelerate_opt.html, -, -
-PERI, Peridynamics models, Mike Parks (Sandia), "pair_style peri"_pair_peri.html, peri, -
-POEMS, coupled rigid body motion, Rudra Mukherjee (JPL), "fix poems"_fix_poems.html, rigid, lib/poems
-PYTHON, embed Python code in an input script, -, "python"_python.html, python, lib/python
-REAX, ReaxFF potential, Aidan Thompson (Sandia), "pair_style reax"_pair_reax.html, reax,  lib/reax
-REPLICA, multi-replica methods, -, "Section_howto 6.5"_Section_howto.html#howto_5, tad, -
-RIGID, rigid bodies, -, "fix rigid"_fix_rigid.html, rigid, -
-SHOCK, shock loading methods, -, "fix msst"_fix_msst.html, -, -
-SNAP, quantum-fit potential, Aidan Thompson (Sandia), "pair snap"_pair_snap.html, snap, -
-SRD, stochastic rotation dynamics, -, "fix srd"_fix_srd.html, srd, -
-VORONOI, Voronoi tesselations, Daniel Schwen (LANL), "compute voronoi/atom"_compute_voronoi_atom.html, -, Voro++
-XTC, dumps in XTC format, -, "dump"_dump.html, -, -
-:tb(ea=c)
-
-The "Authors" column lists a name(s) if a specific person is
-responible for creating and maintaining the package.
-More details on
-multiple authors are give below.
-
-(1) The FLD package was created by Amit Kumar and Michael Bybee from
-Jonathan Higdon's group at UIUC.
-
-(2) The OPT package was created by James Fischer (High Performance
-Technologies), David Richie, and Vincent Natoli (Stone Ridge
-Technolgy).
-
-(3) The KIM package was created by Valeriu Smirichinski, Ryan Elliott,
-and Ellad Tadmor (U Minn).
-
-(4) The KOKKOS package was created primarily by Christian Trott
-(Sandia).  It uses the Kokkos library which was developed by Carter
-Edwards, Christian, and collaborators at Sandia.
-
-The "Doc page" column links to either a portion of the
-"Section_howto"_Section_howto.html of the manual, or an input script
-command implemented as part of the package.
-
-The "Example" column is a sub-directory in the examples directory of
-the distribution which has an input script that uses the package.
-E.g. "peptide" refers to the examples/peptide directory.
-
-The "Library" column lists an external library which must be built
-first and which LAMMPS links to when it is built.  If it is listed as
-lib/package, then the code for the library is under the lib directory
-of the LAMMPS distribution.  See the lib/package/README file for info
-on how to build the library.  If it is not listed as lib/package, then
-it is a third-party library not included in the LAMMPS distribution.
-See the src/package/README or src/package/Makefile.lammps file for
-info on where to download the library.  "Section
-start"_Section_start.html#start_3_3 of the manual also gives details
-on how to build LAMMPS with both kinds of auxiliary libraries.
-
-Except where explained below, all of these packages can be installed,
-and LAMMPS re-built, by issuing these commands from the src dir.
-
-make yes-package
-make machine
-or
-Make.py -p package -a machine :pre
-
-To un-install the package and re-build LAMMPS without it:
-
-make no-package
-make machine
-or
-Make.py -p ^package -a machine :pre
-
-"Package" is the name of the package in lower-case letters,
-e.g. asphere or rigid, and "machine" is the build target, e.g. mpi or
-serial.
-
-:line
-:line
-
-Build instructions for COMPRESS package :h4
-
-:line
-
-Build instructions for GPU package :h4
-
-:line
-
-Build instructions for KIM package :h4
-
-:line
-
-Build instructions for KOKKOS package :h4
-
-:line
-
-Build instructions for KSPACE package :h4
-
-:line
-
-Build instructions for MEAM package :h4
-
-:line
-
-Build instructions for POEMS package :h4
-
-:line
-
-Build instructions for PYTHON package :h4
-
-:line
-
-Build instructions for REAX package :h4
-
-:line
-
-Build instructions for VORONOI package :h4
-
-:line
-
-Build instructions for XTC package :h4
-
-:line
-:line
-
-4.2 User packages :h4,link(pkg_2)
-
-The current list of user-contributed packages is as follows:
-
-Package, Description, Author(s), Doc page, Example, Pic/movie, Library
-USER-ATC, atom-to-continuum coupling, Jones & Templeton & Zimmerman (1), "fix atc"_fix_atc.html, USER/atc, "atc"_atc, lib/atc
-USER-AWPMD, wave-packet MD, Ilya Valuev (JIHT), "pair_style awpmd/cut"_pair_awpmd.html, USER/awpmd, -, lib/awpmd
-USER-CG-CMM, coarse-graining model, Axel Kohlmeyer (Temple U), "pair_style lj/sdk"_pair_sdk.html, USER/cg-cmm, "cg"_cg, -
-USER-COLVARS, collective variables, Fiorin & Henin & Kohlmeyer (2), "fix colvars"_fix_colvars.html, USER/colvars, "colvars"_colvars, lib/colvars
-USER-CUDA, NVIDIA GPU styles, Christian Trott (U Tech Ilmenau), "Section accelerate"_accelerate_cuda.html, USER/cuda, -, lib/cuda
-USER-DIFFRACTION, virutal x-ray and electron diffraction, Shawn Coleman (ARL),"compute xrd"_compute_xrd.html, USER/diffraction, -, -
-USER-DRUDE, Drude oscillators, Dequidt & Devemy & Padua (3), "tutorial"_tutorial_drude.html, USER/drude, -, -
-USER-EFF, electron force field, Andres Jaramillo-Botero (Caltech), "pair_style eff/cut"_pair_eff.html, USER/eff, "eff"_eff, -
-USER-FEP, free energy perturbation, Agilio Padua (U Blaise Pascal Clermont-Ferrand), "compute fep"_compute_fep.html, USER/fep, -, -
-USER-H5MD, dump output via HDF5, Pierre de Buyl (KU Leuven), "dump h5md"_dump_h5md.html, -, -, lib/h5md
-USER-INTEL, Vectorized CPU and Intel(R) coprocessor styles, W. Michael Brown (Intel), "Section accelerate"_accelerate_intel.html, examples/intel, -, -
-USER-LB, Lattice Boltzmann fluid, Colin Denniston (U Western Ontario), "fix lb/fluid"_fix_lb_fluid.html, USER/lb, -, -
-USER-MGPT, fast MGPT multi-ion potentials, Tomas Oppelstrup & John Moriarty (LLNL), "pair_style mgpt"_pair_mgpt.html, USER/mgpt, -, -
-USER-MISC, single-file contributions, USER-MISC/README, USER-MISC/README, -, -, -
-USER-MOLFILE, "VMD"_VMD molfile plug-ins, Axel Kohlmeyer (Temple U), "dump molfile"_dump_molfile.html, -, -, VMD-MOLFILE
-USER-OMP, OpenMP threaded styles, Axel Kohlmeyer (Temple U), "Section accelerate"_accelerate_omp.html, -, -, -
-USER-PHONON, phonon dynamical matrix, Ling-Ti Kong (Shanghai Jiao Tong U), "fix phonon"_fix_phonon.html, USER/phonon, -, -
-USER-QMMM, QM/MM coupling, Axel Kohlmeyer (Temple U), "fix qmmm"_fix_qmmm.html, USER/qmmm, -, lib/qmmm
-USER-QTB, quantum nuclear effects, Yuan Shen (Stanford), "fix qtb"_fix_qtb.html "fix_qbmsst"_fix_qbmsst.html, qtb, -, -
-USER-QUIP, QUIP/libatoms interface, Albert Bartok-Partay (U Cambridge), "pair_style quip"_pair_quip.html, USER/quip, -, lib/quip
-USER-REAXC, C version of ReaxFF, Metin Aktulga (LBNL), "pair_style reaxc"_pair_reax_c.html, reax, -, -
-USER-SMD, smoothed Mach dynamics, Georg Ganzenmuller (EMI), "userguide.pdf"_PDF/SMD_LAMMPS_userguide.pdf, USER/smd, -, -
-USER-SMTBQ, Second Moment Tight Binding - QEq potential, Salles & Maras & Politano & Tetot (4), "pair_style smtbq"_pair_smtbq.html, USER/smtbq, -, -
-USER-SPH, smoothed particle hydrodynamics, Georg Ganzenmuller (EMI), "userguide.pdf"_PDF/SPH_LAMMPS_userguide.pdf, USER/sph, "sph"_sph, -
-USER-TALLY, Pairwise tallied computes, Axel Kohlmeyer (Temple U), "compute <...>/tally"_compute_tally.html, USER/tally, -, -
-:tb(ea=c)
-
-:link(atc,http://lammps.sandia.gov/pictures.html#atc)
-:link(cg,http://lammps.sandia.gov/pictures.html#cg)
-:link(eff,http://lammps.sandia.gov/movies.html#eff)
-:link(sph,http://lammps.sandia.gov/movies.html#sph)
-:link(VMD,http://www.ks.uiuc.edu/Research/vmd)
-
-The "Authors" column lists a name(s) if a specific person is
-responible for creating and maintaining the package.
-
-(1) The ATC package was created by Reese Jones, Jeremy Templeton, and
-Jon Zimmerman (Sandia).
-
-(2) The COLVARS package was created by Axel Kohlmeyer (Temple U) using
-the colvars module library written by Giacomo Fiorin (Temple U) and
-Jerome Henin (LISM, Marseille, France).
-
-(3) The DRUDE package was created by Alain Dequidt (U Blaise Pascal
-Clermont-Ferrand) and co-authors Julien Devemy (CNRS) and Agilio Padua
-(U Blaise Pascal).
-
-(4) The SMTBQ package was created by Nicolas Salles, Emile Maras,
-Olivier Politano, and Robert Tetot (LAAS-CNRS, France).
-
-If the Library is not listed as lib/package, then it is a third-party
-library not included in the LAMMPS distribution.  See the
-src/package/Makefile.lammps file for info on where to download the
-library from.
-
-The "Doc page" column links to either a portion of the
-"Section_howto"_Section_howto.html of the manual, or an input script
-command implemented as part of the package, or to additional
-documentation provided within the package.
-
-The "Example" column is a sub-directory in the examples directory of
-the distribution which has an input script that uses the package.
-E.g. "peptide" refers to the examples/peptide directory.  USER/cuda
-refers to the examples/USER/cuda directory.
-
-The "Library" column lists an external library which must be built
-first and which LAMMPS links to when it is built.  If it is listed as
-lib/package, then the code for the library is under the lib directory
-of the LAMMPS distribution.  See the lib/package/README file for info
-on how to build the library.  If it is not listed as lib/package, then
-it is a third-party library not included in the LAMMPS distribution.
-See the src/package/Makefile.lammps file for info on where to download
-the library.  "Section start"_Section_start.html#start_3_3 of the
-manual also gives details on how to build LAMMPS with both kinds of
-auxiliary libraries.
-
-Except where explained below, all of these packages can be installed,
-and LAMMPS re-built, by issuing these commands from the src dir.
-
-make yes-user-package
-make machine
-or
-Make.py -p package -a machine :pre
-
-To un-install the package and re-build LAMMPS without it:
-
-make no-user-package
-make machine
-or
-Make.py -p ^package -a machine :pre
-
-"Package" is the name of the package (in this case without the user
-prefix) in lower-case letters, e.g. drude or phonon, and "machine" is
-the build target, e.g. mpi or serial.
-
-:line
-:line
-
-USER-ATC package :h4
-
-This package implements a "fix atc" command which can be used in a
-LAMMPS input script.  This fix can be employed to either do concurrent
-coupling of MD with FE-based physics surrogates or on-the-fly
-post-processing of atomic information to continuum fields.
-
-See the doc page for the fix atc command to get started.  At the
-bottom of the doc page are many links to additional documentation
-contained in the doc/USER/atc directory.
-
-There are example scripts for using this package in examples/USER/atc.
-
-This package uses an external library in lib/atc which must be
-compiled before making LAMMPS.  See the lib/atc/README file and the
-LAMMPS manual for information on building LAMMPS with external
-libraries.
-
-The primary people who created this package are Reese Jones (rjones at
-sandia.gov), Jeremy Templeton (jatempl at sandia.gov) and Jon
-Zimmerman (jzimmer at sandia.gov) at Sandia.  Contact them directly if
-you have questions.
-
-:line
-
-USER-AWPMD package :h4
-
-This package contains a LAMMPS implementation of the Antisymmetrized
-Wave Packet Molecular Dynamics (AWPMD) method.
-
-See the doc page for the pair_style awpmd/cut command to get started.
-
-There are example scripts for using this package in examples/USER/awpmd.
-
-This package uses an external library in lib/awpmd which must be
-compiled before making LAMMPS.  See the lib/awpmd/README file and the
-LAMMPS manual for information on building LAMMPS with external
-libraries.
-
-The person who created this package is Ilya Valuev at the JIHT in
-Russia (valuev at physik.hu-berlin.de).  Contact him directly if you
-have questions.
-
-:line
-
-USER-CG-CMM package :h4
-
-This package implements 3 commands which can be used in a LAMMPS input
-script:
-
-pair_style lj/sdk
-pair_style lj/sdk/coul/long
-angle_style sdk :ul
-
-These styles allow coarse grained MD simulations with the
-parametrization of Shinoda, DeVane, Klein, Mol Sim, 33, 27 (2007)
-(SDK), with extensions to simulate ionic liquids, electrolytes, lipids
-and charged amino acids.
-
-See the doc pages for these commands for details.
-
-There are example scripts for using this package in
-examples/USER/cg-cmm.
-
-This is the second generation implementation reducing the the clutter
-of the previous version. For many systems with electrostatics, it will
-be faster to use pair_style hybrid/overlay with lj/sdk and coul/long
-instead of the combined lj/sdk/coul/long style.  since the number of
-charged atom types is usually small.  For any other coulomb
-interactions this is now required.  To exploit this property, the use
-of the kspace_style pppm/cg is recommended over regular pppm. For all
-new styles, input file backward compatibility is provided.  The old
-implementation is still available through appending the /old
-suffix. These will be discontinued and removed after the new
-implementation has been fully validated.
-
-The current version of this package should be considered beta
-quality. The CG potentials work correctly for "normal" situations, but
-have not been testing with all kinds of potential parameters and
-simulation systems.
-
-The person who created this package is Axel Kohlmeyer at Temple U
-(akohlmey at gmail.com).  Contact him directly if you have questions.
-
-:line
-
-USER-COLVARS package :h4
-
-This package implements the "fix colvars" command which can be
-used in a LAMMPS input script.
-
-This fix allows to use "collective variables" to implement
-Adaptive Biasing Force, Metadynamics, Steered MD, Umbrella
-Sampling and Restraints. This code consists of two parts:
-
-A portable collective variable module library written and maintained
-by Giacomo Fiorin (ICMS, Temple University, Philadelphia, PA, USA) and
-Jerome Henin (LISM, CNRS, Marseille, France). This code is located in
-the directory lib/colvars and needs to be compiled first.  The colvars
-fix and an interface layer, exchanges information between LAMMPS and
-the collective variable module. :ul
-
-See the doc page of "fix colvars"_fix_colvars.html for more details.
-
-There are example scripts for using this package in
-examples/USER/colvars
-
-This is a very new interface that does not yet support all
-features in the module and will see future optimizations
-and improvements. The colvars module library is also available
-in NAMD has been thoroughly used and tested there. Bugs and
-problems are likely due to the interface layers code.
-Thus the current version of this package should be considered
-beta quality.
-
-The person who created this package is Axel Kohlmeyer at Temple U
-(akohlmey at gmail.com).  Contact him directly if you have questions.
-
-:line
-
-USER-CUDA package :h4
-
-This package provides acceleration of various LAMMPS pair styles, fix
-styles, compute styles, and long-range Coulombics via PPPM for NVIDIA
-GPUs.
- 
-See this section of the manual to get started:
-
-"Section_accelerate"_Section_accelerate.html#acc_7
-
-There are example scripts for using this package in
-examples/USER/cuda.
-
-This package uses an external library in lib/cuda which must be
-compiled before making LAMMPS.  See the lib/cuda/README file and the
-LAMMPS manual for information on building LAMMPS with external
-libraries.
-
-The person who created this package is Christian Trott at the
-University of Technology Ilmenau, Germany (christian.trott at
-tu-ilmenau.de).  Contact him directly if you have questions.
-
-:line
-
-USER-DIFFRACTION package :h4
-
-This package contains the commands neeed to calculate x-ray and
-electron diffraction intensities based on kinematic diffraction 
-theory.
-
-See these doc pages and their related commands to get started:
-
-"compute xrd"_compute_xrd.html
-"compute saed"_compute_saed.html
-"fix saed/vtk"_fix_saed_vtk.html :ul
-
-The person who created this package is Shawn P. Coleman 
-(shawn.p.coleman8.ctr at mail.mil) while at the University of 
-Arkansas.  Contact him directly if you have questions.
-
-:line
-
-USER-DRUDE package :h4
-
-This package implements methods for simulating polarizable systems
-in LAMMPS using thermalized Drude oscillators.
-
-See these doc pages and their related commands to get started:
-
-"Drude tutorial"_tutorial_drude.html
-"fix drude"_fix_drude.html
-"compute temp/drude"_compute_temp_drude.html
-"fix langevin/drude"_fix_langevin_drude.html
-"fix drude/transform/..."_fix_drude_transform.html
-"pair thole"_pair_thole.html :ul
-
-There are auxiliary tools for using this package in tools/drude.
-
-The person who created this package is Alain Dequidt at Universite
-Blaise Pascal Clermont-Ferrand (alain.dequidt at univ-bpclermont.fr)
-Contact him directly if you have questions. Co-authors: Julien Devemy,
-Agilio Padua.
-
-:line
-
-USER-EFF package :h4
-
-This package contains a LAMMPS implementation of the electron Force
-Field (eFF) currently under development at Caltech, as described in
-A. Jaramillo-Botero, J. Su, Q. An, and W.A. Goddard III, JCC,
-2010. The eFF potential was first introduced by Su and Goddard, in
-2007.
-
-eFF can be viewed as an approximation to QM wave packet dynamics and
-Fermionic molecular dynamics, combining the ability of electronic
-structure methods to describe atomic structure, bonding, and chemistry
-in materials, and of plasma methods to describe nonequilibrium
-dynamics of large systems with a large number of highly excited
-electrons. We classify it as a mixed QM-classical approach rather than
-a conventional force field method, which introduces QM-based terms (a
-spin-dependent repulsion term to account for the Pauli exclusion
-principle and the electron wavefunction kinetic energy associated with
-the Heisenberg principle) that reduce, along with classical
-electrostatic terms between nuclei and electrons, to the sum of a set
-of effective pairwise potentials.  This makes eFF uniquely suited to
-simulate materials over a wide range of temperatures and pressures
-where electronically excited and ionized states of matter can occur
-and coexist.
-
-The necessary customizations to the LAMMPS core are in place to
-enable the correct handling of explicit electron properties during
-minimization and dynamics.
-
-See the doc page for the pair_style eff/cut command to get started.
-
-There are example scripts for using this package in
-examples/USER/eff.
-
-There are auxiliary tools for using this package in tools/eff.
-
-The person who created this package is Andres Jaramillo-Botero at
-CalTech (ajaramil at wag.caltech.edu).  Contact him directly if you
-have questions.
-
-:line
-
-USER-FEP package :h4
-
-This package provides methods for performing free energy perturbation
-simulations with soft-core pair potentials in LAMMPS.
-
-See these doc pages and their related commands to get started:
-
-"fix adapt/fep"_fix_adapt_fep.html
-"compute fep"_compute_fep.html
-"soft pair styles"_pair_lj_soft.html :ul
-
-The person who created this package is Agilio Padua at Universite
-Blaise Pascal Clermont-Ferrand (agilio.padua at univ-bpclermont.fr)
-Contact him directly if you have questions.
-
-:line
-
-USER-H5MD package :h4
-
-This package contains a "dump h5md"_dump_h5md.html command for
-performing a dump of atom properties in HDF5 format.  "HDF5
-files"_HDF5 are binary, portable and self-describing and can be
-examined and used by a variety of auxiliary tools.  The output HDF5
-files are structured in a format called H5MD, which was designed to
-store molecular data, and can be used and produced by various MD and
-MD-related codes.  The "dump h5md"_doc/dump_h5md.html command gives a
-citation to a paper describing the format.
-
-:link(HDF5,http://www.hdfgroup.org/HDF5/)
-
-The person who created this package and the underlying H5MD format is
-Pierre de Buyl at KU Leuven (see http://pdebuyl.be).  Contact him
-directly if you have questions.
-
-:line
-
-USER-INTEL package :h4
-
-This package provides options for performing neighbor list and
-non-bonded force calculations in single, mixed, or double precision
-and also a capability for accelerating calculations with an
-Intel(R) Xeon Phi(TM) coprocessor.
- 
-See this section of the manual to get started:
-
-"Section_accelerate"_Section_accelerate.html#acc_9
-
-The person who created this package is W. Michael Brown at Intel
-(michael.w.brown at intel.com).  Contact him directly if you have questions.
-
-:line
-
-USER-LB package :h4
-
-This package contains a LAMMPS implementation of a background
-Lattice-Boltzmann fluid, which can be used to model MD particles
-influenced by hydrodynamic forces.
-
-See this doc page and its related commands to get started:
-
-"fix lb/fluid"_fix_lb_fluid.html
-
-The people who created this package are Frances Mackay (fmackay at
-uwo.ca) and Colin (cdennist at uwo.ca) Denniston, University of
-Western Ontario.  Contact them directly if you have questions.
-
-:line
-
-USER-MGPT package :h4
-
-This package contains a fast implementation for LAMMPS of
-quantum-based MGPT multi-ion potentials.  The MGPT or model GPT method
-derives from first-principles DFT-based generalized pseudopotential
-theory (GPT) through a series of systematic approximations valid for
-mid-period transition metals with nearly half-filled d bands.  The
-MGPT method was originally developed by John Moriarty at Lawrence
-Livermore National Lab (LLNL).
-
-In the general matrix representation of MGPT, which can also be
-applied to f-band actinide metals, the multi-ion potentials are
-evaluated on the fly during a simulation through d- or f-state matrix
-multiplication, and the forces that move the ions are determined
-analytically.  The {mgpt} pair style in this package calculates forces
-and energies using an optimized matrix-MGPT algorithm due to Tomas
-Oppelstrup at LLNL.
-
-See this doc page to get started:
-
-"pair_style mgpt"_pair_mgpt.html
-
-The persons who created the USER-MGPT package are Tomas Oppelstrup
-(oppelstrup2@llnl.gov) and John Moriarty (moriarty2@llnl.gov)
-Contact them directly if you have any questions.
-
-:line
-
-USER-MISC package :h4
-
-The files in this package are a potpourri of (mostly) unrelated
-features contributed to LAMMPS by users.  Each feature is a single
-pair of files (*.cpp and *.h).
-
-More information about each feature can be found by reading its doc
-page in the LAMMPS doc directory.  The doc page which lists all LAMMPS
-input script commands is as follows:
-
-"Section_commands"_Section_commands.html#cmd_5
-
-User-contributed features are listed at the bottom of the fix,
-compute, pair, etc sections.
-
-The list of features and author of each is given in the
-src/USER-MISC/README file.
-
-You should contact the author directly if you have specific questions
-about the feature or its coding.
-
-:line
-
-USER-MOLFILE package :h4
-
-This package contains a dump molfile command which uses molfile
-plugins that are bundled with the
-"VMD"_http://www.ks.uiuc.edu/Research/vmd molecular visualization and
-analysis program, to enable LAMMPS to dump its information in formats
-compatible with various molecular simulation tools.
-
-The package only provides the interface code, not the plugins.  These
-can be obtained from a VMD installation which has to match the
-platform that you are using to compile LAMMPS for. By adding plugins
-to VMD, support for new file formats can be added to LAMMPS (or VMD or
-other programs that use them) without having to recompile the
-application itself.
-
-See this doc page to get started:
-
-"dump molfile"_dump_molfile.html#acc_5
-
-The person who created this package is Axel Kohlmeyer at Temple U
-(akohlmey at gmail.com).  Contact him directly if you have questions.
-
-:line
-
-USER-OMP package :h4
-
-This package provides OpenMP multi-threading support and
-other optimizations of various LAMMPS pair styles, dihedral
-styles, and fix styles.
- 
-See this section of the manual to get started:
-
-"Section_accelerate"_Section_accelerate.html#acc_5
-
-The person who created this package is Axel Kohlmeyer at Temple U
-(akohlmey at gmail.com).  Contact him directly if you have questions.
-
-:line
-
-USER-PHONON package :h4
-
-This package contains a fix phonon command that calculates dynamical
-matrices, which can then be used to compute phonon dispersion
-relations, directly from molecular dynamics simulations.
-
-See this doc page to get started:
-
-"fix phonon"_fix_phonon.html
-
-The person who created this package is Ling-Ti Kong (konglt at
-sjtu.edu.cn) at Shanghai Jiao Tong University.  Contact him directly
-if you have questions.
-
-:line
-
-USER-QMMM package :h4
-
-This package provides a fix qmmm command which allows LAMMPS to be
-used in a QM/MM simulation, currently only in combination with pw.x
-code from the "Quantum ESPRESSO"_espresso package.
-
-:link(espresso,http://www.quantum-espresso.org)
-
-The current implementation only supports an ONIOM style mechanical
-coupling to the Quantum ESPRESSO plane wave DFT package.
-Electrostatic coupling is in preparation and the interface has been
-written in a manner that coupling to other QM codes should be possible
-without changes to LAMMPS itself.
-
-See this doc page to get started:
-
-"fix qmmm"_fix_qmmm.html
-
-as well as the lib/qmmm/README file.
-
-The person who created this package is Axel Kohlmeyer at Temple U
-(akohlmey at gmail.com).  Contact him directly if you have questions.
-
-:line
-
-USER-QTB package :h4
-
-This package provides a self-consistent quantum treatment of the
-vibrational modes in a classical molecular dynamics simulation.  By
-coupling the MD simulation to a colored thermostat, it introduces zero
-point energy into the system, alter the energy power spectrum and the
-heat capacity towards their quantum nature. This package could be of
-interest if one wants to model systems at temperatures lower than
-their classical limits or when temperatures ramp up across the
-classical limits in the simulation.
-
-See these two doc pages to get started:
-
-"fix qtb"_fix_qtb.html provides quantum nulcear correction through a
-colored thermostat and can be used with other time integration schemes
-like "fix nve"_fix_nve.html or "fix nph"_fix_nh.html.
-
-"fix qbmsst"_fix_qbmsst.html enables quantum nuclear correction of a
-multi-scale shock technique simulation by coupling the quantum thermal
-bath with the shocked system.
-
-The person who created this package is Yuan Shen (sy0302 at
-stanford.edu) at Stanford University.  Contact him directly if you
-have questions.
-
-:line
-
-USER-REAXC package :h4
-
-This package contains a implementation for LAMMPS of the ReaxFF force
-field.  ReaxFF uses distance-dependent bond-order functions to
-represent the contributions of chemical bonding to the potential
-energy.  It was originally developed by Adri van Duin and the Goddard
-group at CalTech.
-
-The USER-REAXC version of ReaxFF (pair_style reax/c), implemented in
-C, should give identical or very similar results to pair_style reax,
-which is a ReaxFF implementation on top of a Fortran library, a
-version of which library was originally authored by Adri van Duin.
-
-The reax/c version should be somewhat faster and more scalable,
-particularly with respect to the charge equilibration calculation.  It
-should also be easier to build and use since there are no complicating
-issues with Fortran memory allocation or linking to a Fortran library.
-
-For technical details about this implemention of ReaxFF, see
-this paper:
-
-Parallel and Scalable Reactive Molecular Dynamics: Numerical Methods
-and Algorithmic Techniques, H. M. Aktulga, J. C. Fogarty,
-S. A. Pandit, A. Y. Grama, Parallel Computing, in press (2011).
-
-See the doc page for the pair_style reax/c command for details
-of how to use it in LAMMPS.
-
-The person who created this package is Hasan Metin Aktulga (hmaktulga
-at lbl.gov), while at Purdue University.  Contact him directly, or
-Aidan Thompson at Sandia (athomps at sandia.gov), if you have
-questions.
-
-:line
-
-USER-SMD package :h4
-
-This package implements smoothed Mach dynamics (SMD) in
-LAMMPS.  Currently, the package has the following features:
-
-* Does liquids via traditional Smooth Particle Hydrodynamics (SPH)
-
-* Also solves solids mechanics problems via a state of the art 
-  stabilized meshless method with hourglass control.
-
-* Can specify hydrostatic interactions independently from material 
-  strength models, i.e. pressure and deviatoric stresses are separated.
-
-* Many material models available (Johnson-Cook, plasticity with 
-  hardening, Mie-Grueneisen, Polynomial EOS).  Easy to add new 
-  material models.
-
-* Rigid boundary conditions (walls) can be loaded as surface geometries 
-  from *.STL files.
-
-See the file doc/PDF/SMD_LAMMPS_userguide.pdf to get started.
-
-There are example scripts for using this package in examples/USER/smd.
-
-The person who created this package is Georg Ganzenmuller at the
-Fraunhofer-Institute for High-Speed Dynamics, Ernst Mach Institute in
-Germany (georg.ganzenmueller at emi.fhg.de).  Contact him directly if
-you have questions.
-
-:line
-
-USER-SMTBQ package :h4
-
-This package implements the Second Moment Tight Binding - QEq (SMTB-Q)
-potential for the description of ionocovalent bonds in oxides.
-
-There are example scripts for using this package in
-examples/USER/smtbq.
-
-See this doc page to get started:
-
-"pair_style smtbq"_pair_smtbq.html
-
-The persons who created the USER-SMTBQ package are Nicolas Salles,
-Emile Maras, Olivier Politano, Robert Tetot, who can be contacted at
-these email addreses: lammps@u-bourgogne.fr, nsalles@laas.fr.  Contact
-them directly if you have any questions.
-
-:line
-
-USER-SPH package :h4
-
-This package implements smoothed particle hydrodynamics (SPH) in
-LAMMPS.  Currently, the package has the following features:
-
-* Tait, ideal gas, Lennard-Jones equation of states, full support for 
-  complete (i.e. internal-energy dependent) equations of state
-
-* Plain or Monaghans XSPH integration of the equations of motion
-
-* Density continuity or density summation to propagate the density field
-
-* Commands to set internal energy and density of particles from the 
-  input script
-
-* Output commands to access internal energy and density for dumping and 
-  thermo output
-
-See the file doc/PDF/SPH_LAMMPS_userguide.pdf to get started.
-
-There are example scripts for using this package in examples/USER/sph.
-
-The person who created this package is Georg Ganzenmuller at the
-Fraunhofer-Institute for High-Speed Dynamics, Ernst Mach Institute in
-Germany (georg.ganzenmueller at emi.fhg.de).  Contact him directly if
-you have questions.

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-  <div class="section" id="performance-scalability">
-<h1>8. Performance &amp; scalability<a class="headerlink" href="#performance-scalability" title="Permalink to this headline">¶</a></h1>
-<p>LAMMPS performance on several prototypical benchmarks and machines is
-discussed on the Benchmarks page of the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a> where
-CPU timings and parallel efficiencies are listed.  Here, the
-benchmarks are described briefly and some useful rules of thumb about
-their performance are highlighted.</p>
-<p>These are the 5 benchmark problems:</p>
-<ol class="arabic simple">
-<li>LJ = atomic fluid, Lennard-Jones potential with 2.5 sigma cutoff (55</li>
-</ol>
-<blockquote>
-<div>neighbors per atom), NVE integration</div></blockquote>
-<ol class="arabic simple">
-<li>Chain = bead-spring polymer melt of 100-mer chains, FENE bonds and LJ
-pairwise interactions with a 2^(1/6) sigma cutoff (5 neighbors per
-atom), NVE integration</li>
-<li>EAM = metallic solid, Cu EAM potential with 4.95 Angstrom cutoff (45
-neighbors per atom), NVE integration</li>
-<li>Chute = granular chute flow, frictional history potential with 1.1
-sigma cutoff (7 neighbors per atom), NVE integration</li>
-<li>Rhodo = rhodopsin protein in solvated lipid bilayer, CHARMM force
-field with a 10 Angstrom LJ cutoff (440 neighbors per atom),
-particle-particle particle-mesh (PPPM) for long-range Coulombics, NPT
-integration</li>
-</ol>
-<p>The input files for running the benchmarks are included in the LAMMPS
-distribution, as are sample output files.  Each of the 5 problems has
-32,000 atoms and runs for 100 timesteps.  Each can be run as a serial
-benchmarks (on one processor) or in parallel.  In parallel, each
-benchmark can be run as a fixed-size or scaled-size problem.  For
-fixed-size benchmarking, the same 32K atom problem is run on various
-numbers of processors.  For scaled-size benchmarking, the model size
-is increased with the number of processors.  E.g. on 8 processors, a
-256K-atom problem is run; on 1024 processors, a 32-million atom
-problem is run, etc.</p>
-<p>A useful metric from the benchmarks is the CPU cost per atom per
-timestep.  Since LAMMPS performance scales roughly linearly with
-problem size and timesteps, the run time of any problem using the same
-model (atom style, force field, cutoff, etc) can then be estimated.
-For example, on a 1.7 GHz Pentium desktop machine (Intel icc compiler
-under Red Hat Linux), the CPU run-time in seconds/atom/timestep for
-the 5 problems is</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="25%" />
-<col width="14%" />
-<col width="14%" />
-<col width="14%" />
-<col width="14%" />
-<col width="17%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td>Problem:</td>
-<td>LJ</td>
-<td>Chain</td>
-<td>EAM</td>
-<td>Chute</td>
-<td>Rhodopsin</td>
-</tr>
-<tr class="row-even"><td>CPU/atom/step:</td>
-<td>4.55E-6</td>
-<td>2.18E-6</td>
-<td>9.38E-6</td>
-<td>2.18E-6</td>
-<td>1.11E-4</td>
-</tr>
-<tr class="row-odd"><td>Ratio to LJ:</td>
-<td>1.0</td>
-<td>0.48</td>
-<td>2.06</td>
-<td>0.48</td>
-<td>24.5</td>
-</tr>
-</tbody>
-</table>
-<p>The ratios mean that if the atomic LJ system has a normalized cost of
-1.0, the bead-spring chains and granular systems run 2x faster, while
-the EAM metal and solvated protein models run 2x and 25x slower
-respectively.  The bulk of these cost differences is due to the
-expense of computing a particular pairwise force field for a given
-number of neighbors per atom.</p>
-<p>Performance on a parallel machine can also be predicted from the
-one-processor timings if the parallel efficiency can be estimated.
-The communication bandwidth and latency of a particular parallel
-machine affects the efficiency.  On most machines LAMMPS will give
-fixed-size parallel efficiencies on these benchmarks above 50% so long
-as the atoms/processor count is a few 100 or greater - i.e. on 64 to
-128 processors.  Likewise, scaled-size parallel efficiencies will
-typically be 80% or greater up to very large processor counts.  The
-benchmark data on the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW Site</a> gives specific examples on
-some different machines, including a run of 3/4 of a billion LJ atoms
-on 1500 processors that ran at 85% parallel efficiency.</p>
-</div>
-
-
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doc/Section_perf.txt

@@ -1,77 +0,0 @@
-"Previous Section"_Section_example.html - "LAMMPS WWW Site"_lws - "LAMMPS Documentation"_ld - "LAMMPS Commands"_lc - "Next Section"_Section_tools.html :c
-
-:link(lws,http://lammps.sandia.gov)
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-
-:line
-
-8. Performance & scalability :h3
-
-LAMMPS performance on several prototypical benchmarks and machines is
-discussed on the Benchmarks page of the "LAMMPS WWW Site"_lws where
-CPU timings and parallel efficiencies are listed.  Here, the
-benchmarks are described briefly and some useful rules of thumb about
-their performance are highlighted.
-
-These are the 5 benchmark problems:
-
-LJ = atomic fluid, Lennard-Jones potential with 2.5 sigma cutoff (55
-neighbors per atom), NVE integration :olb,l
-
-Chain = bead-spring polymer melt of 100-mer chains, FENE bonds and LJ
-pairwise interactions with a 2^(1/6) sigma cutoff (5 neighbors per
-atom), NVE integration :l
-
-EAM = metallic solid, Cu EAM potential with 4.95 Angstrom cutoff (45
-neighbors per atom), NVE integration :l
-
-Chute = granular chute flow, frictional history potential with 1.1
-sigma cutoff (7 neighbors per atom), NVE integration :l
-
-Rhodo = rhodopsin protein in solvated lipid bilayer, CHARMM force
-field with a 10 Angstrom LJ cutoff (440 neighbors per atom),
-particle-particle particle-mesh (PPPM) for long-range Coulombics, NPT
-integration :ole,l
-
-The input files for running the benchmarks are included in the LAMMPS
-distribution, as are sample output files.  Each of the 5 problems has
-32,000 atoms and runs for 100 timesteps.  Each can be run as a serial
-benchmarks (on one processor) or in parallel.  In parallel, each
-benchmark can be run as a fixed-size or scaled-size problem.  For
-fixed-size benchmarking, the same 32K atom problem is run on various
-numbers of processors.  For scaled-size benchmarking, the model size
-is increased with the number of processors.  E.g. on 8 processors, a
-256K-atom problem is run; on 1024 processors, a 32-million atom
-problem is run, etc.
-
-A useful metric from the benchmarks is the CPU cost per atom per
-timestep.  Since LAMMPS performance scales roughly linearly with
-problem size and timesteps, the run time of any problem using the same
-model (atom style, force field, cutoff, etc) can then be estimated.
-For example, on a 1.7 GHz Pentium desktop machine (Intel icc compiler
-under Red Hat Linux), the CPU run-time in seconds/atom/timestep for
-the 5 problems is
-
-Problem:, LJ, Chain, EAM, Chute, Rhodopsin
-CPU/atom/step:, 4.55E-6, 2.18E-6, 9.38E-6, 2.18E-6, 1.11E-4
-Ratio to LJ:, 1.0, 0.48, 2.06, 0.48, 24.5 :tb(ea=c,ca1=r)
-
-The ratios mean that if the atomic LJ system has a normalized cost of
-1.0, the bead-spring chains and granular systems run 2x faster, while
-the EAM metal and solvated protein models run 2x and 25x slower
-respectively.  The bulk of these cost differences is due to the
-expense of computing a particular pairwise force field for a given
-number of neighbors per atom.
-
-Performance on a parallel machine can also be predicted from the
-one-processor timings if the parallel efficiency can be estimated.
-The communication bandwidth and latency of a particular parallel
-machine affects the efficiency.  On most machines LAMMPS will give
-fixed-size parallel efficiencies on these benchmarks above 50% so long
-as the atoms/processor count is a few 100 or greater - i.e. on 64 to
-128 processors.  Likewise, scaled-size parallel efficiencies will
-typically be 80% or greater up to very large processor counts.  The
-benchmark data on the "LAMMPS WWW Site"_lws gives specific examples on
-some different machines, including a run of 3/4 of a billion LJ atoms
-on 1500 processors that ran at 85% parallel efficiency.

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-<li class="toctree-l1 current"><a class="current reference internal" href="">11. Python interface to LAMMPS</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="#overview-of-running-lammps-from-python">11.1. Overview of running LAMMPS from Python</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#overview-of-using-python-from-a-lammps-script">11.2. Overview of using Python from a LAMMPS script</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#building-lammps-as-a-shared-library">11.3. Building LAMMPS as a shared library</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#installing-the-python-wrapper-into-python">11.4. Installing the Python wrapper into Python</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#extending-python-with-mpi-to-run-in-parallel">11.5. Extending Python with MPI to run in parallel</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#testing-the-python-lammps-interface">11.6. Testing the Python-LAMMPS interface</a><ul>
-<li class="toctree-l3"><a class="reference internal" href="#test-lammps-and-python-in-serial">11.6.1. <strong>Test LAMMPS and Python in serial:</strong></a></li>
-<li class="toctree-l3"><a class="reference internal" href="#test-lammps-and-python-in-parallel">11.6.2. <strong>Test LAMMPS and Python in parallel:</strong></a></li>
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-  <div class="section" id="python-interface-to-lammps">
-<h1>11. Python interface to LAMMPS<a class="headerlink" href="#python-interface-to-lammps" title="Permalink to this headline">¶</a></h1>
-<p>LAMMPS can work together with Python in two ways.  First, Python can
-wrap LAMMPS through the <a class="reference internal" href="Section_howto.html#howto-19"><span>LAMMPS library interface</span></a>, so that a Python script can
-create one or more instances of LAMMPS and launch one or more
-simulations.  In Python lingo, this is &#8220;extending&#8221; Python with LAMMPS.</p>
-<p>Second, LAMMPS can use the Python interpreter, so that a LAMMPS input
-script can invoke Python code, and pass information back-and-forth
-between the input script and Python functions you write.  The Python
-code can also callback to LAMMPS to query or change its attributes.
-In Python lingo, this is &#8220;embedding&#8221; Python in LAMMPS.</p>
-<p>This section describes how to do both.</p>
-<ul class="simple">
-<li>11.1 <a class="reference internal" href="#py-1"><span>Overview of running LAMMPS from Python</span></a></li>
-<li>11.2 <a class="reference internal" href="#py-2"><span>Overview of using Python from a LAMMPS script</span></a></li>
-<li>11.3 <a class="reference internal" href="#py-3"><span>Building LAMMPS as a shared library</span></a></li>
-<li>11.4 <a class="reference internal" href="#py-4"><span>Installing the Python wrapper into Python</span></a></li>
-<li>11.5 <a class="reference internal" href="#py-5"><span>Extending Python with MPI to run in parallel</span></a></li>
-<li>11.6 <a class="reference internal" href="#py-6"><span>Testing the Python-LAMMPS interface</span></a></li>
-<li>11.7 <a class="reference internal" href="#py-7"><span>Using LAMMPS from Python</span></a></li>
-<li>11.8 <a class="reference internal" href="#py-8"><span>Example Python scripts that use LAMMPS</span></a></li>
-</ul>
-<p>If you are not familiar with it, <a class="reference external" href="http://www.python.org">Python</a> is a
-powerful scripting and programming language which can essentially do
-anything that faster, lower-level languages like C or C++ can do, but
-typically with much fewer lines of code.  When used in embedded mode,
-Python can perform operations that the simplistic LAMMPS input script
-syntax cannot.  Python can be also be used as a &#8220;glue&#8221; language to
-drive a program through its library interface, or to hook multiple
-pieces of software together, such as a simulation package plus a
-visualization package, or to run a coupled multiscale or multiphysics
-model.</p>
-<p>See <a class="reference internal" href="Section_howto.html#howto-10"><span>Section_howto 10</span></a> of the manual and
-the couple directory of the distribution for more ideas about coupling
-LAMMPS to other codes.  See <a class="reference internal" href="Section_howto.html#howto-19"><span>Section_howto 19</span></a> for a description of the LAMMPS
-library interface provided in src/library.cpp and src/library.h, and
-how to extend it for your needs.  As described below, that interface
-is what is exposed to Python either when calling LAMMPS from Python or
-when calling Python from a LAMMPS input script and then calling back
-to LAMMPS from Python code.  The library interface is designed to be
-easy to add functions to.  Thus the Python interface to LAMMPS is also
-easy to extend as well.</p>
-<p>If you create interesting Python scripts that run LAMMPS or
-interesting Python functions that can be called from a LAMMPS input
-script, that you think would be useful to other users, please <a class="reference external" href="http://lammps.sandia.gov/authors.html">email them to the developers</a>.  We can
-include them in the LAMMPS distribution.</p>
-<div class="section" id="overview-of-running-lammps-from-python">
-<span id="py-1"></span><h2>11.1. Overview of running LAMMPS from Python<a class="headerlink" href="#overview-of-running-lammps-from-python" title="Permalink to this headline">¶</a></h2>
-<p>The LAMMPS distribution includes a python directory with all you need
-to run LAMMPS from Python.  The python/lammps.py file wraps the LAMMPS
-library interface, with one wrapper function per LAMMPS library
-function.  This file makes it is possible to do the following either
-from a Python script, or interactively from a Python prompt: create
-one or more instances of LAMMPS, invoke LAMMPS commands or give it an
-input script, run LAMMPS incrementally, extract LAMMPS results, an
-modify internal LAMMPS variables.  From a Python script you can do
-this in serial or parallel.  Running Python interactively in parallel
-does not generally work, unless you have a version of Python that
-extends standard Python to enable multiple instances of Python to read
-what you type.</p>
-<p>To do all of this, you must first build LAMMPS as a shared library,
-then insure that your Python can find the python/lammps.py file and
-the shared library.  These steps are explained in subsequent sections
-11.3 and 11.4.  Sections 11.5 and 11.6 discuss using MPI from a
-parallel Python program and how to test that you are ready to use
-LAMMPS from Python.  Section 11.7 lists all the functions in the
-current LAMMPS library interface and how to call them from Python.</p>
-<p>Section 11.8 gives some examples of coupling LAMMPS to other tools via
-Python.  For example, LAMMPS can easily be coupled to a GUI or other
-visualization tools that display graphs or animations in real time as
-LAMMPS runs.  Examples of such scripts are inlcluded in the python
-directory.</p>
-<p>Two advantages of using Python to run LAMMPS are how concise the
-language is, and that it can be run interactively, enabling rapid
-development and debugging of programs.  If you use it to mostly invoke
-costly operations within LAMMPS, such as running a simulation for a
-reasonable number of timesteps, then the overhead cost of invoking
-LAMMPS thru Python will be negligible.</p>
-<p>The Python wrapper for LAMMPS uses the amazing and magical (to me)
-&#8220;ctypes&#8221; package in Python, which auto-generates the interface code
-needed between Python and a set of C interface routines for a library.
-Ctypes is part of standard Python for versions 2.5 and later.  You can
-check which version of Python you have installed, by simply typing
-&#8220;python&#8221; at a shell prompt.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="overview-of-using-python-from-a-lammps-script">
-<span id="py-2"></span><h2>11.2. Overview of using Python from a LAMMPS script<a class="headerlink" href="#overview-of-using-python-from-a-lammps-script" title="Permalink to this headline">¶</a></h2>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">It is not currently possible to use the
-<a class="reference internal" href="python.html"><em>python</em></a> command described in this section with Python 3,
-only with Python 2.  The C API changed from Python 2 to 3 and the
-LAMMPS code is not compatible with both.</p>
-</div>
-<p>LAMMPS has a <a class="reference internal" href="python.html"><em>python</em></a> command which can be used in an
-input script to define and execute a Python function that you write
-the code for.  The Python function can also be assigned to a LAMMPS
-python-style variable via the <a class="reference internal" href="variable.html"><em>variable</em></a> command.  Each
-time the variable is evaluated, either in the LAMMPS input script
-itself, or by another LAMMPS command that uses the variable, this will
-trigger the Python function to be invoked.</p>
-<p>The Python code for the function can be included directly in the input
-script or in an auxiliary file.  The function can have arguments which
-are mapped to LAMMPS variables (also defined in the input script) and
-it can return a value to a LAMMPS variable.  This is thus a mechanism
-for your input script to pass information to a piece of Python code,
-ask Python to execute the code, and return information to your input
-script.</p>
-<p>Note that a Python function can be arbitrarily complex.  It can import
-other Python modules, instantiate Python classes, call other Python
-functions, etc.  The Python code that you provide can contain more
-code than the single function.  It can contain other functions or
-Python classes, as well as global variables or other mechanisms for
-storing state between calls from LAMMPS to the function.</p>
-<p>The Python function you provide can consist of &#8220;pure&#8221; Python code that
-only performs operations provided by standard Python.  However, the
-Python function can also &#8220;call back&#8221; to LAMMPS through its
-Python-wrapped library interface, in the manner described in the
-previous section 11.1.  This means it can issue LAMMPS input script
-commands or query and set internal LAMMPS state.  As an example, this
-can be useful in an input script to create a more complex loop with
-branching logic, than can be created using the simple looping and
-brancing logic enabled by the <a class="reference internal" href="next.html"><em>next</em></a> and <a class="reference internal" href="if.html"><em>if</em></a>
-commands.</p>
-<p>See the <a class="reference internal" href="python.html"><em>python</em></a> doc page and the <a class="reference internal" href="variable.html"><em>variable</em></a>
-doc page for its python-style variables for more info, including
-examples of Python code you can write for both pure Python operations
-and callbacks to LAMMPS.</p>
-<p>To run pure Python code from LAMMPS, you only need to build LAMMPS
-with the PYTHON package installed:</p>
-<p>make yes-python
-make machine</p>
-<p>Note that this will link LAMMPS with the Python library on your
-system, which typically requires several auxiliary system libraries to
-also be linked.  The list of these libraries and the paths to find
-them are specified in the lib/python/Makefile.lammps file.  You need
-to insure that file contains the correct information for your version
-of Python and your machine to successfully build LAMMPS.  See the
-lib/python/README file for more info.</p>
-<p>If you want to write Python code with callbacks to LAMMPS, then you
-must also follow the steps overviewed in the preceeding section (11.1)
-for running LAMMPS from Python.  I.e. you must build LAMMPS as a
-shared library and insure that Python can find the python/lammps.py
-file and the shared library.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="building-lammps-as-a-shared-library">
-<span id="py-3"></span><h2>11.3. Building LAMMPS as a shared library<a class="headerlink" href="#building-lammps-as-a-shared-library" title="Permalink to this headline">¶</a></h2>
-<p>Instructions on how to build LAMMPS as a shared library are given in
-<a class="reference internal" href="Section_start.html#start-5"><span>Section_start 5</span></a>.  A shared library is one
-that is dynamically loadable, which is what Python requires to wrap
-LAMMPS.  On Linux this is a library file that ends in &#8221;.so&#8221;, not &#8221;.a&#8221;.</p>
-<p>&gt;From the src directory, type</p>
-<div class="highlight-python"><div class="highlight"><pre>make foo mode=shlib
-</pre></div>
-</div>
-<p>where foo is the machine target name, such as linux or g++ or serial.
-This should create the file liblammps_foo.so in the src directory, as
-well as a soft link liblammps.so, which is what the Python wrapper will
-load by default.  Note that if you are building multiple machine
-versions of the shared library, the soft link is always set to the
-most recently built version.</p>
-<p>If this fails, see <a class="reference internal" href="Section_start.html#start-5"><span>Section_start 5</span></a> for
-more details, especially if your LAMMPS build uses auxiliary libraries
-like MPI or FFTW which may not be built as shared libraries on your
-system.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="installing-the-python-wrapper-into-python">
-<span id="py-4"></span><h2>11.4. Installing the Python wrapper into Python<a class="headerlink" href="#installing-the-python-wrapper-into-python" title="Permalink to this headline">¶</a></h2>
-<p>For Python to invoke LAMMPS, there are 2 files it needs to know about:</p>
-<ul class="simple">
-<li>python/lammps.py</li>
-<li>src/liblammps.so</li>
-</ul>
-<p>Lammps.py is the Python wrapper on the LAMMPS library interface.
-Liblammps.so is the shared LAMMPS library that Python loads, as
-described above.</p>
-<p>You can insure Python can find these files in one of two ways:</p>
-<ul class="simple">
-<li>set two environment variables</li>
-<li>run the python/install.py script</li>
-</ul>
-<p>If you set the paths to these files as environment variables, you only
-have to do it once.  For the csh or tcsh shells, add something like
-this to your ~/.cshrc file, one line for each of the two files:</p>
-<div class="highlight-python"><div class="highlight"><pre>setenv PYTHONPATH ${PYTHONPATH}:/home/sjplimp/lammps/python
-setenv LD_LIBRARY_PATH ${LD_LIBRARY_PATH}:/home/sjplimp/lammps/src
-</pre></div>
-</div>
-<p>If you use the python/install.py script, you need to invoke it every
-time you rebuild LAMMPS (as a shared library) or make changes to the
-python/lammps.py file.</p>
-<p>You can invoke install.py from the python directory as</p>
-<div class="highlight-python"><div class="highlight"><pre>% python install.py [libdir] [pydir]
-</pre></div>
-</div>
-<p>The optional libdir is where to copy the LAMMPS shared library to; the
-default is /usr/local/lib.  The optional pydir is where to copy the
-lammps.py file to; the default is the site-packages directory of the
-version of Python that is running the install script.</p>
-<p>Note that libdir must be a location that is in your default
-LD_LIBRARY_PATH, like /usr/local/lib or /usr/lib.  And pydir must be a
-location that Python looks in by default for imported modules, like
-its site-packages dir.  If you want to copy these files to
-non-standard locations, such as within your own user space, you will
-need to set your PYTHONPATH and LD_LIBRARY_PATH environment variables
-accordingly, as above.</p>
-<p>If the install.py script does not allow you to copy files into system
-directories, prefix the python command with &#8220;sudo&#8221;.  If you do this,
-make sure that the Python that root runs is the same as the Python you
-run.  E.g. you may need to do something like</p>
-<div class="highlight-python"><div class="highlight"><pre>% sudo /usr/local/bin/python install.py [libdir] [pydir]
-</pre></div>
-</div>
-<p>You can also invoke install.py from the make command in the src
-directory as</p>
-<div class="highlight-python"><div class="highlight"><pre>% make install-python
-</pre></div>
-</div>
-<p>In this mode you cannot append optional arguments.  Again, you may
-need to prefix this with &#8220;sudo&#8221;.  In this mode you cannot control
-which Python is invoked by root.</p>
-<p>Note that if you want Python to be able to load different versions of
-the LAMMPS shared library (see <a class="reference internal" href="#py-5"><span>this section</span></a> below), you will
-need to manually copy files like liblammps_g++.so into the appropriate
-system directory.  This is not needed if you set the LD_LIBRARY_PATH
-environment variable as described above.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="extending-python-with-mpi-to-run-in-parallel">
-<span id="py-5"></span><h2>11.5. Extending Python with MPI to run in parallel<a class="headerlink" href="#extending-python-with-mpi-to-run-in-parallel" title="Permalink to this headline">¶</a></h2>
-<p>If you wish to run LAMMPS in parallel from Python, you need to extend
-your Python with an interface to MPI.  This also allows you to
-make MPI calls directly from Python in your script, if you desire.</p>
-<p>There are several Python packages available that purport to wrap MPI
-as a library and allow MPI functions to be called from Python.</p>
-<p>These include</p>
-<ul class="simple">
-<li><a class="reference external" href="http://pympi.sourceforge.net/">pyMPI</a></li>
-<li><a class="reference external" href="http://code.google.com/p/maroonmpi/">maroonmpi</a></li>
-<li><a class="reference external" href="http://code.google.com/p/mpi4py/">mpi4py</a></li>
-<li><a class="reference external" href="http://nbcr.sdsc.edu/forum/viewtopic.php?t=89&amp;sid=c997fefc3933bd66204875b436940f16">myMPI</a></li>
-<li><a class="reference external" href="http://code.google.com/p/pypar">Pypar</a></li>
-</ul>
-<p>All of these except pyMPI work by wrapping the MPI library and
-exposing (some portion of) its interface to your Python script.  This
-means Python cannot be used interactively in parallel, since they do
-not address the issue of interactive input to multiple instances of
-Python running on different processors.  The one exception is pyMPI,
-which alters the Python interpreter to address this issue, and (I
-believe) creates a new alternate executable (in place of &#8220;python&#8221;
-itself) as a result.</p>
-<p>In principle any of these Python/MPI packages should work to invoke
-LAMMPS in parallel and to make MPI calls themselves from a Python
-script which is itself running in parallel.  However, when I
-downloaded and looked at a few of them, their documentation was
-incomplete and I had trouble with their installation.  It&#8217;s not clear
-if some of the packages are still being actively developed and
-supported.</p>
-<p>The one I recommend, since I have successfully used it with LAMMPS, is
-Pypar.  Pypar requires the ubiquitous <a class="reference external" href="http://numpy.scipy.org">Numpy package</a> be installed in your Python.  After
-launching python, type</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">numpy</span>
-</pre></div>
-</div>
-<p>to see if it is installed.  If not, here is how to install it (version
-1.3.0b1 as of April 2009).  Unpack the numpy tarball and from its
-top-level directory, type</p>
-<div class="highlight-python"><div class="highlight"><pre>python setup.py build
-sudo python setup.py install
-</pre></div>
-</div>
-<p>The &#8220;sudo&#8221; is only needed if required to copy Numpy files into your
-Python distribution&#8217;s site-packages directory.</p>
-<p>To install Pypar (version pypar-2.1.4_94 as of Aug 2012), unpack it
-and from its &#8220;source&#8221; directory, type</p>
-<div class="highlight-python"><div class="highlight"><pre>python setup.py build
-sudo python setup.py install
-</pre></div>
-</div>
-<p>Again, the &#8220;sudo&#8221; is only needed if required to copy Pypar files into
-your Python distribution&#8217;s site-packages directory.</p>
-<p>If you have successully installed Pypar, you should be able to run
-Python and type</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">pypar</span>
-</pre></div>
-</div>
-<p>without error.  You should also be able to run python in parallel
-on a simple test script</p>
-<div class="highlight-python"><div class="highlight"><pre>% mpirun -np 4 python test.py
-</pre></div>
-</div>
-<p>where test.py contains the lines</p>
-<div class="highlight-python"><div class="highlight"><pre>import pypar
-print &quot;Proc %d out of %d procs&quot; % (pypar.rank(),pypar.size())
-</pre></div>
-</div>
-<p>and see one line of output for each processor you run on.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">To use Pypar and LAMMPS in parallel from Python, you
-must insure both are using the same version of MPI.  If you only have
-one MPI installed on your system, this is not an issue, but it can be
-if you have multiple MPIs.  Your LAMMPS build is explicit about which
-MPI it is using, since you specify the details in your lo-level
-src/MAKE/Makefile.foo file.  Pypar uses the &#8220;mpicc&#8221; command to find
-information about the MPI it uses to build against.  And it tries to
-load &#8220;libmpi.so&#8221; from the LD_LIBRARY_PATH.  This may or may not find
-the MPI library that LAMMPS is using.  If you have problems running
-both Pypar and LAMMPS together, this is an issue you may need to
-address, e.g. by moving other MPI installations so that Pypar finds
-the right one.</p>
-</div>
-<hr class="docutils" />
-</div>
-<div class="section" id="testing-the-python-lammps-interface">
-<span id="py-6"></span><h2>11.6. Testing the Python-LAMMPS interface<a class="headerlink" href="#testing-the-python-lammps-interface" title="Permalink to this headline">¶</a></h2>
-<p>To test if LAMMPS is callable from Python, launch Python interactively
-and type:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">lammps</span> <span class="kn">import</span> <span class="n">lammps</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">()</span>
-</pre></div>
-</div>
-<p>If you get no errors, you&#8217;re ready to use LAMMPS from Python.  If the
-2nd command fails, the most common error to see is</p>
-<div class="highlight-python"><div class="highlight"><pre>OSError: Could not load LAMMPS dynamic library
-</pre></div>
-</div>
-<p>which means Python was unable to load the LAMMPS shared library.  This
-typically occurs if the system can&#8217;t find the LAMMPS shared library or
-one of the auxiliary shared libraries it depends on, or if something
-about the library is incompatible with your Python.  The error message
-should give you an indication of what went wrong.</p>
-<p>You can also test the load directly in Python as follows, without
-first importing from the lammps.py file:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ctypes</span> <span class="kn">import</span> <span class="n">CDLL</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">CDLL</span><span class="p">(</span><span class="s">&quot;liblammps.so&quot;</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>If an error occurs, carefully go thru the steps in <a class="reference internal" href="Section_start.html#start-5"><span>Section_start 5</span></a> and above about building a shared
-library and about insuring Python can find the necessary two files
-it needs.</p>
-<div class="section" id="test-lammps-and-python-in-serial">
-<h3>11.6.1. <strong>Test LAMMPS and Python in serial:</strong><a class="headerlink" href="#test-lammps-and-python-in-serial" title="Permalink to this headline">¶</a></h3>
-<p>To run a LAMMPS test in serial, type these lines into Python
-interactively from the bench directory:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">lammps</span> <span class="kn">import</span> <span class="n">lammps</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">()</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">lmp</span><span class="o">.</span><span class="n">file</span><span class="p">(</span><span class="s">&quot;in.lj&quot;</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>Or put the same lines in the file test.py and run it as</p>
-<div class="highlight-python"><div class="highlight"><pre>% python test.py
-</pre></div>
-</div>
-<p>Either way, you should see the results of running the in.lj benchmark
-on a single processor appear on the screen, the same as if you had
-typed something like:</p>
-<div class="highlight-python"><div class="highlight"><pre>lmp_g++ -in in.lj
-</pre></div>
-</div>
-</div>
-<div class="section" id="test-lammps-and-python-in-parallel">
-<h3>11.6.2. <strong>Test LAMMPS and Python in parallel:</strong><a class="headerlink" href="#test-lammps-and-python-in-parallel" title="Permalink to this headline">¶</a></h3>
-<p>To run LAMMPS in parallel, assuming you have installed the
-<a class="reference external" href="http://datamining.anu.edu.au/~ole/pypar">Pypar</a> package as discussed
-above, create a test.py file containing these lines:</p>
-<div class="highlight-python"><div class="highlight"><pre>import pypar
-from lammps import lammps
-lmp = lammps()
-lmp.file(&quot;in.lj&quot;)
-print &quot;Proc %d out of %d procs has&quot; % (pypar.rank(),pypar.size()),lmp
-pypar.finalize()
-</pre></div>
-</div>
-<p>You can then run it in parallel as:</p>
-<div class="highlight-python"><div class="highlight"><pre>% mpirun -np 4 python test.py
-</pre></div>
-</div>
-<p>and you should see the same output as if you had typed</p>
-<div class="highlight-python"><div class="highlight"><pre>% mpirun -np 4 lmp_g++ -in in.lj
-</pre></div>
-</div>
-<p>Note that if you leave out the 3 lines from test.py that specify Pypar
-commands you will instantiate and run LAMMPS independently on each of
-the P processors specified in the mpirun command.  In this case you
-should get 4 sets of output, each showing that a LAMMPS run was made
-on a single processor, instead of one set of output showing that
-LAMMPS ran on 4 processors.  If the 1-processor outputs occur, it
-means that Pypar is not working correctly.</p>
-<p>Also note that once you import the PyPar module, Pypar initializes MPI
-for you, and you can use MPI calls directly in your Python script, as
-described in the Pypar documentation.  The last line of your Python
-script should be pypar.finalize(), to insure MPI is shut down
-correctly.</p>
-</div>
-<div class="section" id="running-python-scripts">
-<h3>11.6.3. <strong>Running Python scripts:</strong><a class="headerlink" href="#running-python-scripts" title="Permalink to this headline">¶</a></h3>
-<p>Note that any Python script (not just for LAMMPS) can be invoked in
-one of several ways:</p>
-<div class="highlight-python"><div class="highlight"><pre>% python foo.script
-% python -i foo.script
-% foo.script
-</pre></div>
-</div>
-<p>The last command requires that the first line of the script be
-something like this:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="c">#!/usr/local/bin/python</span>
-<span class="c">#!/usr/local/bin/python -i</span>
-</pre></div>
-</div>
-<p>where the path points to where you have Python installed, and that you
-have made the script file executable:</p>
-<div class="highlight-python"><div class="highlight"><pre>% chmod +x foo.script
-</pre></div>
-</div>
-<p>Without the &#8220;-i&#8221; flag, Python will exit when the script finishes.
-With the &#8220;-i&#8221; flag, you will be left in the Python interpreter when
-the script finishes, so you can type subsequent commands.  As
-mentioned above, you can only run Python interactively when running
-Python on a single processor, not in parallel.</p>
-</div>
-</div>
-<div class="section" id="using-lammps-from-python">
-<span id="py-7"></span><h2>11.7. Using LAMMPS from Python<a class="headerlink" href="#using-lammps-from-python" title="Permalink to this headline">¶</a></h2>
-<p>As described above, the Python interface to LAMMPS consists of a
-Python &#8220;lammps&#8221; module, the source code for which is in
-python/lammps.py, which creates a &#8220;lammps&#8221; object, with a set of
-methods that can be invoked on that object.  The sample Python code
-below assumes you have first imported the &#8220;lammps&#8221; module in your
-Python script, as follows:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="kn">from</span> <span class="nn">lammps</span> <span class="kn">import</span> <span class="n">lammps</span>
-</pre></div>
-</div>
-<p>These are the methods defined by the lammps module.  If you look at
-the files src/library.cpp and src/library.h you will see that they
-correspond one-to-one with calls you can make to the LAMMPS library
-from a C++ or C or Fortran program.</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">()</span>           <span class="c"># create a LAMMPS object using the default liblammps.so library</span>
-<span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">(</span><span class="n">ptr</span><span class="o">=</span><span class="n">lmpptr</span><span class="p">)</span> <span class="c"># ditto, but use lmpptr as previously created LAMMPS object</span>
-<span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">(</span><span class="s">&quot;g++&quot;</span><span class="p">)</span>      <span class="c"># create a LAMMPS object using the liblammps_g++.so library</span>
-<span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">(</span><span class="s">&quot;&quot;</span><span class="p">,</span><span class="nb">list</span><span class="p">)</span>    <span class="c"># ditto, with command-line args, e.g. list = [&quot;-echo&quot;,&quot;screen&quot;]</span>
-<span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">(</span><span class="s">&quot;g++&quot;</span><span class="p">,</span><span class="nb">list</span><span class="p">)</span>
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">lmp</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>              <span class="c"># destroy a LAMMPS object</span>
-</pre></div>
-</div>
-<p>version = lmp.version()  # return the numerical version id, e.g. LAMMPS 2 Sep 2015 -&gt; 20150902</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">lmp</span><span class="o">.</span><span class="n">file</span><span class="p">(</span><span class="nb">file</span><span class="p">)</span>           <span class="c"># run an entire input script, file = &quot;in.lj&quot;</span>
-<span class="n">lmp</span><span class="o">.</span><span class="n">command</span><span class="p">(</span><span class="n">cmd</span><span class="p">)</span>         <span class="c"># invoke a single LAMMPS command, cmd = &quot;run 100&quot;</span>
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">xlo</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">extract_global</span><span class="p">(</span><span class="n">name</span><span class="p">,</span><span class="nb">type</span><span class="p">)</span>  <span class="c"># extract a global quantity</span>
-                                     <span class="c"># name = &quot;boxxlo&quot;, &quot;nlocal&quot;, etc</span>
-                                  <span class="c"># type = 0 = int</span>
-                                  <span class="c">#        1 = double</span>
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">coords</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">extract_atom</span><span class="p">(</span><span class="n">name</span><span class="p">,</span><span class="nb">type</span><span class="p">)</span>      <span class="c"># extract a per-atom quantity</span>
-                                          <span class="c"># name = &quot;x&quot;, &quot;type&quot;, etc</span>
-                                       <span class="c"># type = 0 = vector of ints</span>
-                                       <span class="c">#        1 = array of ints</span>
-                                       <span class="c">#        2 = vector of doubles</span>
-                                       <span class="c">#        3 = array of doubles</span>
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">eng</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">extract_compute</span><span class="p">(</span><span class="nb">id</span><span class="p">,</span><span class="n">style</span><span class="p">,</span><span class="nb">type</span><span class="p">)</span>  <span class="c"># extract value(s) from a compute</span>
-<span class="n">v3</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">extract_fix</span><span class="p">(</span><span class="nb">id</span><span class="p">,</span><span class="n">style</span><span class="p">,</span><span class="nb">type</span><span class="p">,</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">)</span>   <span class="c"># extract value(s) from a fix</span>
-                                          <span class="c"># id = ID of compute or fix</span>
-                                       <span class="c"># style = 0 = global data</span>
-                                       <span class="c">#         1 = per-atom data</span>
-                                       <span class="c">#         2 = local data</span>
-                                       <span class="c"># type = 0 = scalar</span>
-                                       <span class="c">#        1 = vector</span>
-                                       <span class="c">#        2 = array</span>
-                                       <span class="c"># i,j = indices of value in global vector or array</span>
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">var</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">extract_variable</span><span class="p">(</span><span class="n">name</span><span class="p">,</span><span class="n">group</span><span class="p">,</span><span class="n">flag</span><span class="p">)</span>  <span class="c"># extract value(s) from a variable</span>
-                                          <span class="c"># name = name of variable</span>
-                                          <span class="c"># group = group ID (ignored for equal-style variables)</span>
-                                          <span class="c"># flag = 0 = equal-style variable</span>
-                                          <span class="c">#        1 = atom-style variable</span>
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">flag</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">set_variable</span><span class="p">(</span><span class="n">name</span><span class="p">,</span><span class="n">value</span><span class="p">)</span>       <span class="c"># set existing named string-style variable to value, flag = 0 if successful</span>
-<span class="n">natoms</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">get_natoms</span><span class="p">()</span>                 <span class="c"># total # of atoms as int</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">lmp</span><span class="o">.</span><span class="n">gather_atoms</span><span class="p">(</span><span class="n">name</span><span class="p">,</span><span class="nb">type</span><span class="p">,</span><span class="n">count</span><span class="p">)</span>  <span class="c"># return atom attribute of all atoms gathered into data, ordered by atom ID</span>
-                                          <span class="c"># name = &quot;x&quot;, &quot;charge&quot;, &quot;type&quot;, etc</span>
-                                          <span class="c"># count = # of per-atom values, 1 or 3, etc</span>
-<span class="n">lmp</span><span class="o">.</span><span class="n">scatter_atoms</span><span class="p">(</span><span class="n">name</span><span class="p">,</span><span class="nb">type</span><span class="p">,</span><span class="n">count</span><span class="p">,</span><span class="n">data</span><span class="p">)</span>   <span class="c"># scatter atom attribute of all atoms from data, ordered by atom ID</span>
-                                          <span class="c"># name = &quot;x&quot;, &quot;charge&quot;, &quot;type&quot;, etc</span>
-                                          <span class="c"># count = # of per-atom values, 1 or 3, etc</span>
-</pre></div>
-</div>
-<hr class="docutils" />
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">Currently, the creation of a LAMMPS object from within
-lammps.py does not take an MPI communicator as an argument.  There
-should be a way to do this, so that the LAMMPS instance runs on a
-subset of processors if desired, but I don&#8217;t know how to do it from
-Pypar.  So for now, it runs with MPI_COMM_WORLD, which is all the
-processors.  If someone figures out how to do this with one or more of
-the Python wrappers for MPI, like Pypar, please let us know and we
-will amend these doc pages.</p>
-</div>
-<p>The lines</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="kn">from</span> <span class="nn">lammps</span> <span class="kn">import</span> <span class="n">lammps</span>
-<span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">()</span>
-</pre></div>
-</div>
-<p>create an instance of LAMMPS, wrapped in a Python class by the lammps
-Python module, and return an instance of the Python class as lmp.  It
-is used to make all subequent calls to the LAMMPS library.</p>
-<p>Additional arguments can be used to tell Python the name of the shared
-library to load or to pass arguments to the LAMMPS instance, the same
-as if LAMMPS were launched from a command-line prompt.</p>
-<p>If the ptr argument is set like this:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">lmp</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">(</span><span class="n">ptr</span><span class="o">=</span><span class="n">lmpptr</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>then lmpptr must be an argument passed to Python via the LAMMPS
-<a class="reference internal" href="python.html"><em>python</em></a> command, when it is used to define a Python
-function that is invoked by the LAMMPS input script.  This mode of
-using Python with LAMMPS is described above in 11.2.  The variable
-lmpptr refers to the instance of LAMMPS that called the embedded
-Python interpreter.  Using it as an argument to lammps() allows the
-returned Python class instance &#8220;lmp&#8221; to make calls to that instance of
-LAMMPS.  See the <a class="reference internal" href="python.html"><em>python</em></a> command doc page for examples
-using this syntax.</p>
-<p>Note that you can create multiple LAMMPS objects in your Python
-script, and coordinate and run multiple simulations, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="kn">from</span> <span class="nn">lammps</span> <span class="kn">import</span> <span class="n">lammps</span>
-<span class="n">lmp1</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">()</span>
-<span class="n">lmp2</span> <span class="o">=</span> <span class="n">lammps</span><span class="p">()</span>
-<span class="n">lmp1</span><span class="o">.</span><span class="n">file</span><span class="p">(</span><span class="s">&quot;in.file1&quot;</span><span class="p">)</span>
-<span class="n">lmp2</span><span class="o">.</span><span class="n">file</span><span class="p">(</span><span class="s">&quot;in.file2&quot;</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>The file() and command() methods allow an input script or single
-commands to be invoked.</p>
-<p>The extract_global(), extract_atom(), extract_compute(),
-extract_fix(), and extract_variable() methods return values or
-pointers to data structures internal to LAMMPS.</p>
-<p>For extract_global() see the src/library.cpp file for the list of
-valid names.  New names could easily be added.  A double or integer is
-returned.  You need to specify the appropriate data type via the type
-argument.</p>
-<p>For extract_atom(), a pointer to internal LAMMPS atom-based data is
-returned, which you can use via normal Python subscripting.  See the
-extract() method in the src/atom.cpp file for a list of valid names.
-Again, new names could easily be added.  A pointer to a vector of
-doubles or integers, or a pointer to an array of doubles (double <a href="#id2"><span class="problematic" id="id3">**</span></a>)
-or integers (int <a href="#id4"><span class="problematic" id="id5">**</span></a>) is returned.  You need to specify the appropriate
-data type via the type argument.</p>
-<p>For extract_compute() and extract_fix(), the global, per-atom, or
-local data calulated by the compute or fix can be accessed.  What is
-returned depends on whether the compute or fix calculates a scalar or
-vector or array.  For a scalar, a single double value is returned.  If
-the compute or fix calculates a vector or array, a pointer to the
-internal LAMMPS data is returned, which you can use via normal Python
-subscripting.  The one exception is that for a fix that calculates a
-global vector or array, a single double value from the vector or array
-is returned, indexed by I (vector) or I and J (array).  I,J are
-zero-based indices.  The I,J arguments can be left out if not needed.
-See <a class="reference internal" href="Section_howto.html#howto-15"><span>Section_howto 15</span></a> of the manual for a
-discussion of global, per-atom, and local data, and of scalar, vector,
-and array data types.  See the doc pages for individual
-<a class="reference internal" href="compute.html"><em>computes</em></a> and <a class="reference internal" href="fix.html"><em>fixes</em></a> for a description of what
-they calculate and store.</p>
-<p>For extract_variable(), an <a class="reference internal" href="variable.html"><em>equal-style or atom-style variable</em></a> is evaluated and its result returned.</p>
-<p>For equal-style variables a single double value is returned and the
-group argument is ignored.  For atom-style variables, a vector of
-doubles is returned, one value per atom, which you can use via normal
-Python subscripting. The values will be zero for atoms not in the
-specified group.</p>
-<p>The get_natoms() method returns the total number of atoms in the
-simulation, as an int.</p>
-<p>The gather_atoms() method returns a ctypes vector of ints or doubles
-as specified by type, of length count*natoms, for the property of all
-the atoms in the simulation specified by name, ordered by count and
-then by atom ID.  The vector can be used via normal Python
-subscripting.  If atom IDs are not consecutively ordered within
-LAMMPS, a None is returned as indication of an error.</p>
-<p>Note that the data structure gather_atoms(&#8220;x&#8221;) returns is different
-from the data structure returned by extract_atom(&#8220;x&#8221;) in four ways.
-(1) Gather_atoms() returns a vector which you index as x[i];
-extract_atom() returns an array which you index as x[i][j].  (2)
-Gather_atoms() orders the atoms by atom ID while extract_atom() does
-not.  (3) Gathert_atoms() returns a list of all atoms in the
-simulation; extract_atoms() returns just the atoms local to each
-processor.  (4) Finally, the gather_atoms() data structure is a copy
-of the atom coords stored internally in LAMMPS, whereas extract_atom()
-returns an array that effectively points directly to the internal
-data.  This means you can change values inside LAMMPS from Python by
-assigning a new values to the extract_atom() array.  To do this with
-the gather_atoms() vector, you need to change values in the vector,
-then invoke the scatter_atoms() method.</p>
-<p>The scatter_atoms() method takes a vector of ints or doubles as
-specified by type, of length count*natoms, for the property of all the
-atoms in the simulation specified by name, ordered by bount and then
-by atom ID.  It uses the vector of data to overwrite the corresponding
-properties for each atom inside LAMMPS.  This requires LAMMPS to have
-its &#8220;map&#8221; option enabled; see the <a class="reference internal" href="atom_modify.html"><em>atom_modify</em></a>
-command for details.  If it is not, or if atom IDs are not
-consecutively ordered, no coordinates are reset.</p>
-<p>The array of coordinates passed to scatter_atoms() must be a ctypes
-vector of ints or doubles, allocated and initialized something like
-this:</p>
-<div class="highlight-python"><div class="highlight"><pre>from ctypes import *
-natoms = lmp.get_natoms()
-n3 = 3*natoms
-x = (n3*c_double)()
-x[0] = x coord of atom with ID 1
-x[1] = y coord of atom with ID 1
-x[2] = z coord of atom with ID 1
-x[3] = x coord of atom with ID 2
-...
-x[n3-1] = z coord of atom with ID natoms
-lmp.scatter_coords(&quot;x&quot;,1,3,x)
-</pre></div>
-</div>
-<p>Alternatively, you can just change values in the vector returned by
-gather_atoms(&#8220;x&#8221;,1,3), since it is a ctypes vector of doubles.</p>
-<hr class="docutils" />
-<p>As noted above, these Python class methods correspond one-to-one with
-the functions in the LAMMPS library interface in src/library.cpp and
-library.h.  This means you can extend the Python wrapper via the
-following steps:</p>
-<ul class="simple">
-<li>Add a new interface function to src/library.cpp and
-src/library.h.</li>
-<li>Rebuild LAMMPS as a shared library.</li>
-<li>Add a wrapper method to python/lammps.py for this interface
-function.</li>
-<li>You should now be able to invoke the new interface function from a
-Python script.  Isn&#8217;t ctypes amazing?</li>
-</ul>
-</div>
-<div class="section" id="example-python-scripts-that-use-lammps">
-<span id="py-8"></span><h2>11.8. Example Python scripts that use LAMMPS<a class="headerlink" href="#example-python-scripts-that-use-lammps" title="Permalink to this headline">¶</a></h2>
-<p>These are the Python scripts included as demos in the python/examples
-directory of the LAMMPS distribution, to illustrate the kinds of
-things that are possible when Python wraps LAMMPS.  If you create your
-own scripts, send them to us and we can include them in the LAMMPS
-distribution.</p>
-<table border="1" class="docutils">
-<colgroup>
-<col width="27%" />
-<col width="73%" />
-</colgroup>
-<tbody valign="top">
-<tr class="row-odd"><td>trivial.py</td>
-<td>read/run a LAMMPS input script thru Python</td>
-</tr>
-<tr class="row-even"><td>demo.py</td>
-<td>invoke various LAMMPS library interface routines</td>
-</tr>
-<tr class="row-odd"><td>simple.py</td>
-<td>mimic operation of couple/simple/simple.cpp in Python</td>
-</tr>
-<tr class="row-even"><td>gui.py</td>
-<td>GUI go/stop/temperature-slider to control LAMMPS</td>
-</tr>
-<tr class="row-odd"><td>plot.py</td>
-<td>real-time temeperature plot with GnuPlot via Pizza.py</td>
-</tr>
-<tr class="row-even"><td>viz_tool.py</td>
-<td>real-time viz via some viz package</td>
-</tr>
-<tr class="row-odd"><td>vizplotgui_tool.py</td>
-<td>combination of viz_tool.py and plot.py and gui.py</td>
-</tr>
-</tbody>
-</table>
-<hr class="docutils" />
-<p>For the viz_tool.py and vizplotgui_tool.py commands, replace &#8220;tool&#8221;
-with &#8220;gl&#8221; or &#8220;atomeye&#8221; or &#8220;pymol&#8221; or &#8220;vmd&#8221;, depending on what
-visualization package you have installed.</p>
-<p>Note that for GL, you need to be able to run the Pizza.py GL tool,
-which is included in the pizza sub-directory.  See the <a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">Pizza.py doc pages</a> for more info:</p>
-<p>Note that for AtomEye, you need version 3, and there is a line in the
-scripts that specifies the path and name of the executable.  See the
-AtomEye WWW pages <a class="reference external" href="http://mt.seas.upenn.edu/Archive/Graphics/A">here</a> or <a class="reference external" href="http://mt.seas.upenn.edu/Archive/Graphics/A3/A3.html">here</a> for more details:</p>
-<div class="highlight-python"><div class="highlight"><pre>http://mt.seas.upenn.edu/Archive/Graphics/A
-http://mt.seas.upenn.edu/Archive/Graphics/A3/A3.html
-</pre></div>
-</div>
-<p>The latter link is to AtomEye 3 which has the scriping
-capability needed by these Python scripts.</p>
-<p>Note that for PyMol, you need to have built and installed the
-open-source version of PyMol in your Python, so that you can import it
-from a Python script.  See the PyMol WWW pages <a class="reference external" href="http://www.pymol.org">here</a> or
-<a class="reference external" href="http://sourceforge.net/scm/?type=svn&amp;group_id=4546">here</a> for more details:</p>
-<div class="highlight-python"><div class="highlight"><pre>http://www.pymol.org
-http://sourceforge.net/scm/?type=svn&amp;group_id=4546
-</pre></div>
-</div>
-<p>The latter link is to the open-source version.</p>
-<p>Note that for VMD, you need a fairly current version (1.8.7 works for
-me) and there are some lines in the pizza/vmd.py script for 4 PIZZA
-variables that have to match the VMD installation on your system.</p>
-<hr class="docutils" />
-<p>See the python/README file for instructions on how to run them and the
-source code for individual scripts for comments about what they do.</p>
-<p>Here are screenshots of the vizplotgui_tool.py script in action for
-different visualization package options.  Click to see larger images:</p>
-<a data-lightbox="group-default"
-                   href="_images/screenshot_gl.jpg"
-                   class=""
-                   title=""
-                   data-title=""
-                   ><img src="_images/screenshot_gl.jpg"
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-                    </a><a data-lightbox="group-default"
-                   href="_images/screenshot_atomeye.jpg"
-                   class=""
-                   title=""
-                   data-title=""
-                   ><img src="_images/screenshot_atomeye.jpg"
-                    class=""
-                    width="25%"
-                    height="auto"
-                    alt=""/>
-                    </a><a data-lightbox="group-default"
-                   href="_images/screenshot_pymol.jpg"
-                   class=""
-                   title=""
-                   data-title=""
-                   ><img src="_images/screenshot_pymol.jpg"
-                    class=""
-                    width="25%"
-                    height="auto"
-                    alt=""/>
-                    </a><a data-lightbox="group-default"
-                   href="_images/screenshot_vmd.jpg"
-                   class=""
-                   title=""
-                   data-title=""
-                   ><img src="_images/screenshot_vmd.jpg"
-                    class=""
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-<li class="toctree-l1"><a class="reference internal" href="Section_intro.html">1. Introduction</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_start.html">2. Getting Started</a></li>
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-<li class="toctree-l1 current"><a class="current reference internal" href="">9. Additional tools</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="#amber2lmp-tool">9.1. amber2lmp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#binary2txt-tool">9.2. binary2txt tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#ch2lmp-tool">9.3. ch2lmp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#chain-tool">9.4. chain tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#colvars-tools">9.5. colvars tools</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#createatoms-tool">9.6. createatoms tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#data2xmovie-tool">9.7. data2xmovie tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#eam-database-tool">9.8. eam database tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#eam-generate-tool">9.9. eam generate tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#eff-tool">9.10. eff tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#emacs-tool">9.11. emacs tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#fep-tool">9.12. fep tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#i-pi-tool">9.13. i-pi tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#ipp-tool">9.14. ipp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#kate-tool">9.15. kate tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#lmp2arc-tool">9.16. lmp2arc tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#lmp2cfg-tool">9.17. lmp2cfg tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#lmp2vmd-tool">9.18. lmp2vmd tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#matlab-tool">9.19. matlab tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#micelle2d-tool">9.20. micelle2d tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#moltemplate-tool">9.21. moltemplate tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#msi2lmp-tool">9.22. msi2lmp tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#phonon-tool">9.23. phonon tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#polymer-bonding-tool">9.24. polymer bonding tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#pymol-asphere-tool">9.25. pymol_asphere tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#python-tool">9.26. python tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#reax-tool">9.27. reax tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#restart2data-tool">9.28. restart2data tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#vim-tool">9.29. vim tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#xmgrace-tool">9.30. xmgrace tool</a></li>
-<li class="toctree-l2"><a class="reference internal" href="#xmovie-tool">9.31. xmovie tool</a></li>
-</ul>
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-  <div class="section" id="additional-tools">
-<h1>9. Additional tools<a class="headerlink" href="#additional-tools" title="Permalink to this headline">¶</a></h1>
-<p>LAMMPS is designed to be a computational kernel for performing
-molecular dynamics computations.  Additional pre- and post-processing
-steps are often necessary to setup and analyze a simulation.  A few
-additional tools are provided with the LAMMPS distribution and are
-described in this section.</p>
-<p>Our group has also written and released a separate toolkit called
-<a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">Pizza.py</a> which provides tools for doing setup, analysis,
-plotting, and visualization for LAMMPS simulations.  Pizza.py is
-written in <a class="reference external" href="http://www.python.org">Python</a> and is available for download from <a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">the Pizza.py WWW site</a>.</p>
-<p>Note that many users write their own setup or analysis tools or use
-other existing codes and convert their output to a LAMMPS input format
-or vice versa.  The tools listed here are included in the LAMMPS
-distribution as examples of auxiliary tools.  Some of them are not
-actively supported by Sandia, as they were contributed by LAMMPS
-users.  If you have problems using them, we can direct you to the
-authors.</p>
-<p>The source code for each of these codes is in the tools sub-directory
-of the LAMMPS distribution.  There is a Makefile (which you may need
-to edit for your platform) which will build several of the tools which
-reside in that directory.  Some of them are larger packages in their
-own sub-directories with their own Makefiles.</p>
-<ul class="simple">
-<li><a class="reference internal" href="#amber"><span>amber2lmp</span></a></li>
-<li><a class="reference internal" href="#binary"><span>binary2txt</span></a></li>
-<li><a class="reference internal" href="#charmm"><span>ch2lmp</span></a></li>
-<li><a class="reference internal" href="#chain"><span>chain</span></a></li>
-<li><a class="reference internal" href="#colvars"><span>colvars</span></a></li>
-<li><a class="reference internal" href="#create"><span>createatoms</span></a></li>
-<li><a class="reference internal" href="#data"><span>data2xmovie</span></a></li>
-<li><a class="reference internal" href="#eamdb"><span>eam database</span></a></li>
-<li><a class="reference internal" href="#eamgn"><span>eam generate</span></a></li>
-<li><a class="reference internal" href="#eff"><span>eff</span></a></li>
-<li><a class="reference internal" href="#emacs"><span>emacs</span></a></li>
-<li><a class="reference internal" href="#fep"><span>fep</span></a></li>
-<li><a class="reference internal" href="fix_ipi.html#ipi"><span>i-pi</span></a></li>
-<li><a class="reference internal" href="#ipp"><span>ipp</span></a></li>
-<li><a class="reference internal" href="#kate"><span>kate</span></a></li>
-<li><a class="reference internal" href="#arc"><span>lmp2arc</span></a></li>
-<li><a class="reference internal" href="#cfg"><span>lmp2cfg</span></a></li>
-<li><a class="reference internal" href="#vmd"><span>lmp2vmd</span></a></li>
-<li><span class="xref std std-ref">matlab</span></li>
-<li><a class="reference internal" href="#micelle"><span>micelle2d</span></a></li>
-<li><a class="reference internal" href="#moltemplate"><span>moltemplate</span></a></li>
-<li><a class="reference internal" href="#msi"><span>msi2lmp</span></a></li>
-<li><a class="reference internal" href="#phonon"><span>phonon</span></a></li>
-<li><a class="reference internal" href="#polybond"><span>polymer bonding</span></a></li>
-<li><span class="xref std std-ref">pymol_asphere</span></li>
-<li><a class="reference internal" href="#pythontools"><span>python</span></a></li>
-<li><a class="reference internal" href="#reax"><span>reax</span></a></li>
-<li><a class="reference internal" href="#restart"><span>restart2data</span></a></li>
-<li><a class="reference internal" href="#vim"><span>vim</span></a></li>
-<li><a class="reference internal" href="#xmgrace"><span>xmgrace</span></a></li>
-<li><a class="reference internal" href="#xmovie"><span>xmovie</span></a></li>
-</ul>
-<hr class="docutils" />
-<div class="section" id="amber2lmp-tool">
-<span id="amber"></span><h2>9.1. amber2lmp tool<a class="headerlink" href="#amber2lmp-tool" title="Permalink to this headline">¶</a></h2>
-<p>The amber2lmp sub-directory contains two Python scripts for converting
-files back-and-forth between the AMBER MD code and LAMMPS.  See the
-README file in amber2lmp for more information.</p>
-<p>These tools were written by Keir Novik while he was at Queen Mary
-University of London.  Keir is no longer there and cannot support
-these tools which are out-of-date with respect to the current LAMMPS
-version (and maybe with respect to AMBER as well).  Since we don&#8217;t use
-these tools at Sandia, you&#8217;ll need to experiment with them and make
-necessary modifications yourself.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="binary2txt-tool">
-<span id="binary"></span><h2>9.2. binary2txt tool<a class="headerlink" href="#binary2txt-tool" title="Permalink to this headline">¶</a></h2>
-<p>The file binary2txt.cpp converts one or more binary LAMMPS dump file
-into ASCII text files.  The syntax for running the tool is</p>
-<div class="highlight-python"><div class="highlight"><pre>binary2txt file1 file2 ...
-</pre></div>
-</div>
-<p>which creates file1.txt, file2.txt, etc.  This tool must be compiled
-on a platform that can read the binary file created by a LAMMPS run,
-since binary files are not compatible across all platforms.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="ch2lmp-tool">
-<span id="charmm"></span><h2>9.3. ch2lmp tool<a class="headerlink" href="#ch2lmp-tool" title="Permalink to this headline">¶</a></h2>
-<p>The ch2lmp sub-directory contains tools for converting files
-back-and-forth between the CHARMM MD code and LAMMPS.</p>
-<p>They are intended to make it easy to use CHARMM as a builder and as a
-post-processor for LAMMPS. Using charmm2lammps.pl, you can convert an
-ensemble built in CHARMM into its LAMMPS equivalent.  Using
-lammps2pdb.pl you can convert LAMMPS atom dumps into pdb files.</p>
-<p>See the README file in the ch2lmp sub-directory for more information.</p>
-<p>These tools were created by Pieter in&#8217;t Veld (pjintve at sandia.gov)
-and Paul Crozier (pscrozi at sandia.gov) at Sandia.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="chain-tool">
-<span id="chain"></span><h2>9.4. chain tool<a class="headerlink" href="#chain-tool" title="Permalink to this headline">¶</a></h2>
-<p>The file chain.f creates a LAMMPS data file containing bead-spring
-polymer chains and/or monomer solvent atoms.  It uses a text file
-containing chain definition parameters as an input.  The created
-chains and solvent atoms can strongly overlap, so LAMMPS needs to run
-the system initially with a &#8220;soft&#8221; pair potential to un-overlap it.
-The syntax for running the tool is</p>
-<div class="highlight-python"><div class="highlight"><pre>chain &lt; def.chain &gt; data.file
-</pre></div>
-</div>
-<p>See the def.chain or def.chain.ab files in the tools directory for
-examples of definition files.  This tool was used to create the
-system for the <a class="reference internal" href="Section_perf.html"><em>chain benchmark</em></a>.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="colvars-tools">
-<span id="colvars"></span><h2>9.5. colvars tools<a class="headerlink" href="#colvars-tools" title="Permalink to this headline">¶</a></h2>
-<p>The colvars directory contains a collection of tools for postprocessing
-data produced by the colvars collective variable library.
-To compile the tools, edit the makefile for your system and run &#8220;make&#8221;.</p>
-<p>Please report problems and issues the colvars library and its tools
-at: <a class="reference external" href="https://github.com/colvars/colvars/issues">https://github.com/colvars/colvars/issues</a></p>
-<p>abf_integrate:</p>
-<p>MC-based integration of multidimensional free energy gradient
-Version 20110511</p>
-<div class="highlight-python"><div class="highlight"><pre>Syntax: ./abf_integrate &lt; filename &gt; [-n &lt; nsteps &gt;] [-t &lt; temp &gt;] [-m [0|1] (metadynamics)] [-h &lt; hill_height &gt;] [-f &lt; variable_hill_factor &gt;]
-</pre></div>
-</div>
-<p>The LAMMPS interface to the colvars collective variable library, as
-well as these tools, were created by Axel Kohlmeyer (akohlmey at
-gmail.com) at ICTP, Italy.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="createatoms-tool">
-<span id="create"></span><h2>9.6. createatoms tool<a class="headerlink" href="#createatoms-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/createatoms directory contains a Fortran program called
-createAtoms.f which can generate a variety of interesting crystal
-structures and geometries and output the resulting list of atom
-coordinates in LAMMPS or other formats.</p>
-<p>See the included Manual.pdf for details.</p>
-<p>The tool is authored by Xiaowang Zhou (Sandia), xzhou at sandia.gov.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="data2xmovie-tool">
-<span id="data"></span><h2>9.7. data2xmovie tool<a class="headerlink" href="#data2xmovie-tool" title="Permalink to this headline">¶</a></h2>
-<p>The file data2xmovie.c converts a LAMMPS data file into a snapshot
-suitable for visualizing with the <a class="reference internal" href="#xmovie"><span>xmovie</span></a> tool, as if it had
-been output with a dump command from LAMMPS itself.  The syntax for
-running the tool is</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">data2xmovie</span> <span class="p">[</span><span class="n">options</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">infile</span> <span class="o">&gt;</span> <span class="n">outfile</span>
-</pre></div>
-</div>
-<p>See the top of the data2xmovie.c file for a discussion of the options.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="eam-database-tool">
-<span id="eamdb"></span><h2>9.8. eam database tool<a class="headerlink" href="#eam-database-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/eam_database directory contains a Fortran program that will
-generate EAM alloy setfl potential files for any combination of 16
-elements: Cu, Ag, Au, Ni, Pd, Pt, Al, Pb, Fe, Mo, Ta, W, Mg, Co, Ti,
-Zr.  The files can then be used with the <a class="reference internal" href="pair_eam.html"><em>pair_style eam/alloy</em></a> command.</p>
-<p>The tool is authored by Xiaowang Zhou (Sandia), xzhou at sandia.gov,
-and is based on his paper:</p>
-<p>X. W. Zhou, R. A. Johnson, and H. N. G. Wadley, Phys. Rev. B, 69,
-144113 (2004).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="eam-generate-tool">
-<span id="eamgn"></span><h2>9.9. eam generate tool<a class="headerlink" href="#eam-generate-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/eam_generate directory contains several one-file C programs
-that convert an analytic formula into a tabulated <a class="reference internal" href="pair_eam.html"><em>embedded atom method (EAM)</em></a> setfl potential file.  The potentials they
-produce are in the potentials directory, and can be used with the
-<a class="reference internal" href="pair_eam.html"><em>pair_style eam/alloy</em></a> command.</p>
-<p>The source files and potentials were provided by Gerolf Ziegenhain
-(gerolf at ziegenhain.com).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="eff-tool">
-<span id="eff"></span><h2>9.10. eff tool<a class="headerlink" href="#eff-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/eff directory contains various scripts for generating
-structures and post-processing output for simulations using the
-electron force field (eFF).</p>
-<p>These tools were provided by Andres Jaramillo-Botero at CalTech
-(ajaramil at wag.caltech.edu).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="emacs-tool">
-<span id="emacs"></span><h2>9.11. emacs tool<a class="headerlink" href="#emacs-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/emacs directory contains a Lips add-on file for Emacs that
-enables a lammps-mode for editing of input scripts when using Emacs,
-with various highlighting options setup.</p>
-<p>These tools were provided by Aidan Thompson at Sandia
-(athomps at sandia.gov).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="fep-tool">
-<span id="fep"></span><h2>9.12. fep tool<a class="headerlink" href="#fep-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/fep directory contains Python scripts useful for
-post-processing results from performing free-energy perturbation
-simulations using the USER-FEP package.</p>
-<p>The scripts were contributed by Agilio Padua (Universite Blaise
-Pascal Clermont-Ferrand), agilio.padua at univ-bpclermont.fr.</p>
-<p>See README file in the tools/fep directory.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="i-pi-tool">
-<span id="ipi"></span><h2>9.13. i-pi tool<a class="headerlink" href="#i-pi-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/i-pi directory contains a version of the i-PI package, with
-all the LAMMPS-unrelated files removed.  It is provided so that it can
-be used with the <a class="reference internal" href="fix_ipi.html"><em>fix ipi</em></a> command to perform
-path-integral molecular dynamics (PIMD).</p>
-<p>The i-PI package was created and is maintained by Michele Ceriotti,
-michele.ceriotti at gmail.com, to interface to a variety of molecular
-dynamics codes.</p>
-<p>See the tools/i-pi/manual.pdf file for an overview of i-PI, and the
-<a class="reference internal" href="fix_ipi.html"><em>fix ipi</em></a> doc page for further details on running PIMD
-calculations with LAMMPS.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="ipp-tool">
-<span id="ipp"></span><h2>9.14. ipp tool<a class="headerlink" href="#ipp-tool" title="Permalink to this headline">¶</a></h2>
-<p>The tools/ipp directory contains a Perl script ipp which can be used
-to facilitate the creation of a complicated file (say, a lammps input
-script or tools/createatoms input file) using a template file.</p>
-<p>ipp was created and is maintained by Reese Jones (Sandia), rjones at
-sandia.gov.</p>
-<p>See two examples in the tools/ipp directory.  One of them is for the
-tools/createatoms tool&#8217;s input file.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="kate-tool">
-<span id="kate"></span><h2>9.15. kate tool<a class="headerlink" href="#kate-tool" title="Permalink to this headline">¶</a></h2>
-<p>The file in the tools/kate directory is an add-on to the Kate editor
-in the KDE suite that allow syntax highlighting of LAMMPS input
-scripts.  See the README.txt file for details.</p>
-<p>The file was provided by Alessandro Luigi Sellerio
-(alessandro.sellerio at ieni.cnr.it).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="lmp2arc-tool">
-<span id="arc"></span><h2>9.16. lmp2arc tool<a class="headerlink" href="#lmp2arc-tool" title="Permalink to this headline">¶</a></h2>
-<p>The lmp2arc sub-directory contains a tool for converting LAMMPS output
-files to the format for Accelrys&#8217; Insight MD code (formerly
-MSI/Biosym and its Discover MD code).  See the README file for more
-information.</p>
-<p>This tool was written by John Carpenter (Cray), Michael Peachey
-(Cray), and Steve Lustig (Dupont).  John is now at the Mayo Clinic
-(jec at mayo.edu), but still fields questions about the tool.</p>
-<p>This tool was updated for the current LAMMPS C++ version by Jeff
-Greathouse at Sandia (jagreat at sandia.gov).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="lmp2cfg-tool">
-<span id="cfg"></span><h2>9.17. lmp2cfg tool<a class="headerlink" href="#lmp2cfg-tool" title="Permalink to this headline">¶</a></h2>
-<p>The lmp2cfg sub-directory contains a tool for converting LAMMPS output
-files into a series of <a href="#id1"><span class="problematic" id="id2">*</span></a>.cfg files which can be read into the
-<a class="reference external" href="http://mt.seas.upenn.edu/Archive/Graphics/A">AtomEye</a> visualizer.  See
-the README file for more information.</p>
-<p>This tool was written by Ara Kooser at Sandia (askoose at sandia.gov).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="lmp2vmd-tool">
-<span id="vmd"></span><h2>9.18. lmp2vmd tool<a class="headerlink" href="#lmp2vmd-tool" title="Permalink to this headline">¶</a></h2>
-<p>The lmp2vmd sub-directory contains a README.txt file that describes
-details of scripts and plugin support within the <a class="reference external" href="http://www.ks.uiuc.edu/Research/vmd">VMD package</a> for visualizing LAMMPS
-dump files.</p>
-<p>The VMD plugins and other supporting scripts were written by Axel
-Kohlmeyer (akohlmey at cmm.chem.upenn.edu) at U Penn.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="matlab-tool">
-<span id="matlab"></span><h2>9.19. matlab tool<a class="headerlink" href="#matlab-tool" title="Permalink to this headline">¶</a></h2>
-<p>The matlab sub-directory contains several <span class="xref std std-ref">MATLAB</span> scripts for
-post-processing LAMMPS output.  The scripts include readers for log
-and dump files, a reader for EAM potential files, and a converter that
-reads LAMMPS dump files and produces CFG files that can be visualized
-with the <a class="reference external" href="http://mt.seas.upenn.edu/Archive/Graphics/A">AtomEye</a>
-visualizer.</p>
-<p>See the README.pdf file for more information.</p>
-<p>These scripts were written by Arun Subramaniyan at Purdue Univ
-(asubrama at purdue.edu).</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="micelle2d-tool">
-<span id="micelle"></span><h2>9.20. micelle2d tool<a class="headerlink" href="#micelle2d-tool" title="Permalink to this headline">¶</a></h2>
-<p>The file micelle2d.f creates a LAMMPS data file containing short lipid
-chains in a monomer solution.  It uses a text file containing lipid
-definition parameters as an input.  The created molecules and solvent
-atoms can strongly overlap, so LAMMPS needs to run the system
-initially with a &#8220;soft&#8221; pair potential to un-overlap it.  The syntax
-for running the tool is</p>
-<div class="highlight-python"><div class="highlight"><pre>micelle2d &lt; def.micelle2d &gt; data.file
-</pre></div>
-</div>
-<p>See the def.micelle2d file in the tools directory for an example of a
-definition file.  This tool was used to create the system for the
-<a class="reference internal" href="Section_example.html"><em>micelle example</em></a>.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="moltemplate-tool">
-<span id="moltemplate"></span><h2>9.21. moltemplate tool<a class="headerlink" href="#moltemplate-tool" title="Permalink to this headline">¶</a></h2>
-<p>The moltemplate sub-directory contains a Python-based tool for
-building molecular systems based on a text-file description, and
-creating LAMMPS data files that encode their molecular topology as
-lists of bonds, angles, dihedrals, etc.  See the README.TXT file for
-more information.</p>
-<p>This tool was written by Andrew Jewett (jewett.aij at gmail.com), who
-supports it.  It has its own WWW page at
-<a class="reference external" href="http://moltemplate.org">http://moltemplate.org</a>.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="msi2lmp-tool">
-<span id="msi"></span><h2>9.22. msi2lmp tool<a class="headerlink" href="#msi2lmp-tool" title="Permalink to this headline">¶</a></h2>
-<p>The msi2lmp sub-directory contains a tool for creating LAMMPS input
-data files from Accelrys&#8217; Insight MD code (formerly MSI/Biosym and
-its Discover MD code).  See the README file for more information.</p>
-<p>This tool was written by John Carpenter (Cray), Michael Peachey
-(Cray), and Steve Lustig (Dupont).  John is now at the Mayo Clinic
-(jec at mayo.edu), but still fields questions about the tool.</p>
-<p>This tool may be out-of-date with respect to the current LAMMPS and
-Insight versions.  Since we don&#8217;t use it at Sandia, you&#8217;ll need to
-experiment with it yourself.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="phonon-tool">
-<span id="phonon"></span><h2>9.23. phonon tool<a class="headerlink" href="#phonon-tool" title="Permalink to this headline">¶</a></h2>
-<p>The phonon sub-directory contains a post-processing tool useful for
-analyzing the output of the <a class="reference internal" href="fix_phonon.html"><em>fix phonon</em></a> command in
-the USER-PHONON package.</p>
-<p>See the README file for instruction on building the tool and what
-library it needs.  And see the examples/USER/phonon directory
-for example problems that can be post-processed with this tool.</p>
-<p>This tool was written by Ling-Ti Kong at Shanghai Jiao Tong
-University.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="polymer-bonding-tool">
-<span id="polybond"></span><h2>9.24. polymer bonding tool<a class="headerlink" href="#polymer-bonding-tool" title="Permalink to this headline">¶</a></h2>
-<p>The polybond sub-directory contains a Python-based tool useful for
-performing &#8220;programmable polymer bonding&#8221;.  The Python file
-lmpsdata.py provides a &#8220;Lmpsdata&#8221; class with various methods which can
-be invoked by a user-written Python script to create data files with
-complex bonding topologies.</p>
-<p>See the Manual.pdf for details and example scripts.</p>
-<p>This tool was written by Zachary Kraus at Georgia Tech.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="pymol-asphere-tool">
-<span id="pymol"></span><h2>9.25. pymol_asphere tool<a class="headerlink" href="#pymol-asphere-tool" title="Permalink to this headline">¶</a></h2>
-<p>The pymol_asphere sub-directory contains a tool for converting a
-LAMMPS dump file that contains orientation info for ellipsoidal
-particles into an input file for the <span class="xref std std-ref">PyMol visualization package</span>.</p>
-<p>Specifically, the tool triangulates the ellipsoids so they can be
-viewed as true ellipsoidal particles within PyMol.  See the README and
-examples directory within pymol_asphere for more information.</p>
-<p>This tool was written by Mike Brown at Sandia.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="python-tool">
-<span id="pythontools"></span><h2>9.26. python tool<a class="headerlink" href="#python-tool" title="Permalink to this headline">¶</a></h2>
-<p>The python sub-directory contains several Python scripts
-that perform common LAMMPS post-processing tasks, such as:</p>
-<ul class="simple">
-<li>extract thermodynamic info from a log file as columns of numbers</li>
-<li>plot two columns of thermodynamic info from a log file using GnuPlot</li>
-<li>sort the snapshots in a dump file by atom ID</li>
-<li>convert multiple <a class="reference internal" href="neb.html"><em>NEB</em></a> dump files into one dump file for viz</li>
-<li>convert dump files into XYZ, CFG, or PDB format for viz by other packages</li>
-</ul>
-<p>These are simple scripts built on <a class="reference external" href="http://www.sandia.gov/~sjplimp/pizza.html">Pizza.py</a> modules.  See the
-README for more info on Pizza.py and how to use these scripts.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="reax-tool">
-<span id="reax"></span><h2>9.27. reax tool<a class="headerlink" href="#reax-tool" title="Permalink to this headline">¶</a></h2>
-<p>The reax sub-directory contains stand-alond codes that can
-post-process the output of the <a class="reference internal" href="fix_reax_bonds.html"><em>fix reax/bonds</em></a>
-command from a LAMMPS simulation using <a class="reference internal" href="pair_reax.html"><em>ReaxFF</em></a>.  See
-the README.txt file for more info.</p>
-<p>These tools were written by Aidan Thompson at Sandia.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="restart2data-tool">
-<span id="restart"></span><h2>9.28. restart2data tool<a class="headerlink" href="#restart2data-tool" title="Permalink to this headline">¶</a></h2>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">This tool is now obsolete and is not included in the
-current LAMMPS distribution.  This is becaues there is now a
-<a class="reference internal" href="write_data.html"><em>write_data</em></a> command, which can create a data file
-from within an input script.  Running LAMMPS with the &#8220;-r&#8221;
-<a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> as follows:</p>
-</div>
-<p>lmp_g++ -r restartfile datafile</p>
-<p>is the same as running a 2-line input script:</p>
-<p>read_restart restartfile
-write_data datafile</p>
-<p>which will produce the same data file that the restart2data tool used
-to create.  The following information is included in case you have an
-older version of LAMMPS which still includes the restart2data tool.</p>
-<p>The file restart2data.cpp converts a binary LAMMPS restart file into
-an ASCII data file.  The syntax for running the tool is</p>
-<div class="highlight-python"><div class="highlight"><pre>restart2data restart-file data-file (input-file)
-</pre></div>
-</div>
-<p>Input-file is optional and if specified will contain LAMMPS input
-commands for the masses and force field parameters, instead of putting
-those in the data-file.  Only a few force field styles currently
-support this option.</p>
-<p>This tool must be compiled on a platform that can read the binary file
-created by a LAMMPS run, since binary files are not compatible across
-all platforms.</p>
-<p>Note that a text data file has less precision than a binary restart
-file.  Hence, continuing a run from a converted data file will
-typically not conform as closely to a previous run as will restarting
-from a binary restart file.</p>
-<p>If a &#8220;%&#8221; appears in the specified restart-file, the tool expects a set
-of multiple files to exist.  See the <a class="reference internal" href="restart.html"><em>restart</em></a> and
-<a class="reference internal" href="write_restart.html"><em>write_restart</em></a> commands for info on how such sets
-of files are written by LAMMPS, and how the files are named.</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="vim-tool">
-<span id="vim"></span><h2>9.29. vim tool<a class="headerlink" href="#vim-tool" title="Permalink to this headline">¶</a></h2>
-<p>The files in the tools/vim directory are add-ons to the VIM editor
-that allow easier editing of LAMMPS input scripts.  See the README.txt
-file for details.</p>
-<p>These files were provided by Gerolf Ziegenhain (gerolf at
-ziegenhain.com)</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="xmgrace-tool">
-<span id="xmgrace"></span><h2>9.30. xmgrace tool<a class="headerlink" href="#xmgrace-tool" title="Permalink to this headline">¶</a></h2>
-<p>The files in the tools/xmgrace directory can be used to plot the
-thermodynamic data in LAMMPS log files via the xmgrace plotting
-package.  There are several tools in the directory that can be used in
-post-processing mode.  The lammpsplot.cpp file can be compiled and
-used to create plots from the current state of a running LAMMPS
-simulation.</p>
-<p>See the README file for details.</p>
-<p>These files were provided by Vikas Varshney (vv0210 at gmail.com)</p>
-<hr class="docutils" />
-</div>
-<div class="section" id="xmovie-tool">
-<span id="xmovie"></span><h2>9.31. xmovie tool<a class="headerlink" href="#xmovie-tool" title="Permalink to this headline">¶</a></h2>
-<p>The xmovie tool is an X-based visualization package that can read
-LAMMPS dump files and animate them.  It is in its own sub-directory
-with the tools directory.  You may need to modify its Makefile so that
-it can find the appropriate X libraries to link against.</p>
-<p>The syntax for running xmovie is</p>
-<div class="highlight-python"><div class="highlight"><pre>xmovie [options] dump.file1 dump.file2 ...
-</pre></div>
-</div>
-<p>If you just type &#8220;xmovie&#8221; you will see a list of options.  Note that
-by default, LAMMPS dump files are in scaled coordinates, so you
-typically need to use the -scale option with xmovie.  When xmovie runs
-it opens a visualization window and a control window.  The control
-options are straightforward to use.</p>
-<p>Xmovie was mostly written by Mike Uttormark (U Wisconsin) while he
-spent a summer at Sandia.  It displays 2d projections of a 3d domain.
-While simple in design, it is an amazingly fast program that can
-render large numbers of atoms very quickly.  It&#8217;s a useful tool for
-debugging LAMMPS input and output and making sure your simulation is
-doing what you think it should.  The animations on the Examples page
-of the <a class="reference external" href="http://lammps.sandia.gov">LAMMPS WWW site</a> were created with xmovie.</p>
-<p>I&#8217;ve lost contact with Mike, so I hope he&#8217;s comfortable with us
-distributing his great tool!</p>
-</div>
-</div>
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-  <p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
-<div class="section" id="user-cuda-package">
-<h1>5.USER-CUDA package<a class="headerlink" href="#user-cuda-package" title="Permalink to this headline">¶</a></h1>
-<p>The USER-CUDA package was developed by Christian Trott (Sandia) while
-at U Technology Ilmenau in Germany.  It provides NVIDIA GPU versions
-of many pair styles, many fixes, a few computes, and for long-range
-Coulombics via the PPPM command.  It has the following general
-features:</p>
-<ul class="simple">
-<li>The package is designed to allow an entire LAMMPS calculation, for
-many timesteps, to run entirely on the GPU (except for inter-processor
-MPI communication), so that atom-based data (e.g. coordinates, forces)
-do not have to move back-and-forth between the CPU and GPU.</li>
-<li>The speed-up advantage of this approach is typically better when the
-number of atoms per GPU is large</li>
-<li>Data will stay on the GPU until a timestep where a non-USER-CUDA fix
-or compute is invoked.  Whenever a non-GPU operation occurs (fix,
-compute, output), data automatically moves back to the CPU as needed.
-This may incur a performance penalty, but should otherwise work
-transparently.</li>
-<li>Neighbor lists are constructed on the GPU.</li>
-<li>The package only supports use of a single MPI task, running on a
-single CPU (core), assigned to each GPU.</li>
-</ul>
-<p>Here is a quick overview of how to use the USER-CUDA package:</p>
-<ul class="simple">
-<li>build the library in lib/cuda for your GPU hardware with desired precision</li>
-<li>include the USER-CUDA package and build LAMMPS</li>
-<li>use the mpirun command to specify 1 MPI task per GPU (on each node)</li>
-<li>enable the USER-CUDA package via the &#8220;-c on&#8221; command-line switch</li>
-<li>specify the # of GPUs per node</li>
-<li>use USER-CUDA styles in your input script</li>
-</ul>
-<p>The latter two steps can be done using the &#8220;-pk cuda&#8221; and &#8220;-sf cuda&#8221;
-<a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> respectively.  Or
-the effect of the &#8220;-pk&#8221; or &#8220;-sf&#8221; switches can be duplicated by adding
-the <a class="reference internal" href="package.html"><em>package cuda</em></a> or <a class="reference internal" href="suffix.html"><em>suffix cuda</em></a> commands
-respectively to your input script.</p>
-<p><strong>Required hardware/software:</strong></p>
-<p>To use this package, you need to have one or more NVIDIA GPUs and
-install the NVIDIA Cuda software on your system:</p>
-<p>Your NVIDIA GPU needs to support Compute Capability 1.3. This list may
-help you to find out the Compute Capability of your card:</p>
-<p><a class="reference external" href="http://en.wikipedia.org/wiki/Comparison_of_Nvidia_graphics_processing_units">http://en.wikipedia.org/wiki/Comparison_of_Nvidia_graphics_processing_units</a></p>
-<p>Install the Nvidia Cuda Toolkit (version 3.2 or higher) and the
-corresponding GPU drivers.  The Nvidia Cuda SDK is not required, but
-we recommend it also be installed.  You can then make sure its sample
-projects can be compiled without problems.</p>
-<p><strong>Building LAMMPS with the USER-CUDA package:</strong></p>
-<p>This requires two steps (a,b): build the USER-CUDA library, then build
-LAMMPS with the USER-CUDA package.</p>
-<p>You can do both these steps in one line, using the src/Make.py script,
-described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.
-Type &#8220;Make.py -h&#8221; for help.  If run from the src directory, this
-command will create src/lmp_cuda using src/MAKE/Makefile.mpi as the
-starting Makefile.machine:</p>
-<div class="highlight-python"><div class="highlight"><pre>Make.py -p cuda -cuda mode=single arch=20 -o cuda -a lib-cuda file mpi
-</pre></div>
-</div>
-<p>Or you can follow these two (a,b) steps:</p>
-<ol class="loweralpha simple">
-<li>Build the USER-CUDA library</li>
-</ol>
-<p>The USER-CUDA library is in lammps/lib/cuda.  If your <em>CUDA</em> toolkit
-is not installed in the default system directoy <em>/usr/local/cuda</em> edit
-the file <em>lib/cuda/Makefile.common</em> accordingly.</p>
-<p>To build the library with the settings in lib/cuda/Makefile.default,
-simply type:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">make</span>
-</pre></div>
-</div>
-<p>To set options when the library is built, type &#8220;make OPTIONS&#8221;, where
-<em>OPTIONS</em> are one or more of the following. The settings will be
-written to the <em>lib/cuda/Makefile.defaults</em> before the build.</p>
-<pre class="literal-block">
-<em>precision=N</em> to set the precision level
-  N = 1 for single precision (default)
-  N = 2 for double precision
-  N = 3 for positions in double precision
-  N = 4 for positions and velocities in double precision
-<em>arch=M</em> to set GPU compute capability
-  M = 35 for Kepler GPUs
-  M = 20 for CC2.0 (GF100/110, e.g. C2050,GTX580,GTX470) (default)
-  M = 21 for CC2.1 (GF104/114,  e.g. GTX560, GTX460, GTX450)
-  M = 13 for CC1.3 (GF200, e.g. C1060, GTX285)
-<em>prec_timer=0/1</em> to use hi-precision timers
-  0 = do not use them (default)
-  1 = use them
-  this is usually only useful for Mac machines
-<em>dbg=0/1</em> to activate debug mode
-  0 = no debug mode (default)
-  1 = yes debug mode
-  this is only useful for developers
-<em>cufft=1</em> for use of the CUDA FFT library
-  0 = no CUFFT support (default)
-  in the future other CUDA-enabled FFT libraries might be supported
-</pre>
-<p>If the build is successful, it will produce the files liblammpscuda.a and
-Makefile.lammps.</p>
-<p>Note that if you change any of the options (like precision), you need
-to re-build the entire library.  Do a &#8220;make clean&#8221; first, followed by
-&#8220;make&#8221;.</p>
-<ol class="loweralpha simple" start="2">
-<li>Build LAMMPS with the USER-CUDA package</li>
-</ol>
-<div class="highlight-python"><div class="highlight"><pre>cd lammps/src
-make yes-user-cuda
-make machine
-</pre></div>
-</div>
-<p>No additional compile/link flags are needed in Makefile.machine.</p>
-<p>Note that if you change the USER-CUDA library precision (discussed
-above) and rebuild the USER-CUDA library, then you also need to
-re-install the USER-CUDA package and re-build LAMMPS, so that all
-affected files are re-compiled and linked to the new USER-CUDA
-library.</p>
-<p><strong>Run with the USER-CUDA package from the command line:</strong></p>
-<p>The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.</p>
-<p>When using the USER-CUDA package, you must use exactly one MPI task
-per physical GPU.</p>
-<p>You must use the &#8220;-c on&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to enable the USER-CUDA package.
-The &#8220;-c on&#8221; switch also issues a default <a class="reference internal" href="package.html"><em>package cuda 1</em></a>
-command which sets various USER-CUDA options to default values, as
-discussed on the <a class="reference internal" href="package.html"><em>package</em></a> command doc page.</p>
-<p>Use the &#8220;-sf cuda&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>,
-which will automatically append &#8220;cuda&#8221; to styles that support it.  Use
-the &#8220;-pk cuda Ng&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to
-set Ng = # of GPUs per node to a different value than the default set
-by the &#8220;-c on&#8221; switch (1 GPU) or change other <a class="reference internal" href="package.html"><em>package cuda</em></a> options.</p>
-<div class="highlight-python"><div class="highlight"><pre>lmp_machine -c on -sf cuda -pk cuda 1 -in in.script                       # 1 MPI task uses 1 GPU
-mpirun -np 2 lmp_machine -c on -sf cuda -pk cuda 2 -in in.script          # 2 MPI tasks use 2 GPUs on a single 16-core (or whatever) node
-mpirun -np 24 -ppn 2 lmp_machine -c on -sf cuda -pk cuda 2 -in in.script  # ditto on 12 16-core nodes
-</pre></div>
-</div>
-<p>The syntax for the &#8220;-pk&#8221; switch is the same as same as the &#8220;package
-cuda&#8221; command.  See the <a class="reference internal" href="package.html"><em>package</em></a> command doc page for
-details, including the default values used for all its options if it
-is not specified.</p>
-<p>Note that the default for the <a class="reference internal" href="package.html"><em>package cuda</em></a> command is
-to set the Newton flag to &#8220;off&#8221; for both pairwise and bonded
-interactions.  This typically gives fastest performance.  If the
-<a class="reference internal" href="newton.html"><em>newton</em></a> command is used in the input script, it can
-override these defaults.</p>
-<p><strong>Or run with the USER-CUDA package by editing an input script:</strong></p>
-<p>The discussion above for the mpirun/mpiexec command and the requirement
-of one MPI task per GPU is the same.</p>
-<p>You must still use the &#8220;-c on&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to enable the USER-CUDA package.</p>
-<p>Use the <a class="reference internal" href="suffix.html"><em>suffix cuda</em></a> command, or you can explicitly add a
-&#8220;cuda&#8221; suffix to individual styles in your input script, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/cuda 2.5
-</pre></div>
-</div>
-<p>You only need to use the <a class="reference internal" href="package.html"><em>package cuda</em></a> command if you
-wish to change any of its option defaults, including the number of
-GPUs/node (default = 1), as set by the &#8220;-c on&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>.</p>
-<p><strong>Speed-ups to expect:</strong></p>
-<p>The performance of a GPU versus a multi-core CPU is a function of your
-hardware, which pair style is used, the number of atoms/GPU, and the
-precision used on the GPU (double, single, mixed).</p>
-<p>See the <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the
-LAMMPS web site for performance of the USER-CUDA package on different
-hardware.</p>
-<p><strong>Guidelines for best performance:</strong></p>
-<ul class="simple">
-<li>The USER-CUDA package offers more speed-up relative to CPU performance
-when the number of atoms per GPU is large, e.g. on the order of tens
-or hundreds of 1000s.</li>
-<li>As noted above, this package will continue to run a simulation
-entirely on the GPU(s) (except for inter-processor MPI communication),
-for multiple timesteps, until a CPU calculation is required, either by
-a fix or compute that is non-GPU-ized, or until output is performed
-(thermo or dump snapshot or restart file).  The less often this
-occurs, the faster your simulation will run.</li>
-</ul>
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>None.</p>
-</div>
-</div>
-
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doc/accelerate_cuda.txt

@@ -1,223 +0,0 @@
-"Previous Section"_Section_packages.html - "LAMMPS WWW Site"_lws -
-"LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
-
-:link(lws,http://lammps.sandia.gov)
-:link(ld,Manual.html)
-:link(lc,Section_commands.html#comm)
-
-:line
-
-"Return to Section accelerate overview"_Section_accelerate.html
-
-5.3.1 USER-CUDA package :h4
-
-The USER-CUDA package was developed by Christian Trott (Sandia) while
-at U Technology Ilmenau in Germany.  It provides NVIDIA GPU versions
-of many pair styles, many fixes, a few computes, and for long-range
-Coulombics via the PPPM command.  It has the following general
-features:
-
-The package is designed to allow an entire LAMMPS calculation, for
-many timesteps, to run entirely on the GPU (except for inter-processor
-MPI communication), so that atom-based data (e.g. coordinates, forces)
-do not have to move back-and-forth between the CPU and GPU. :ulb,l
-
-The speed-up advantage of this approach is typically better when the
-number of atoms per GPU is large :l
-
-Data will stay on the GPU until a timestep where a non-USER-CUDA fix
-or compute is invoked.  Whenever a non-GPU operation occurs (fix,
-compute, output), data automatically moves back to the CPU as needed.
-This may incur a performance penalty, but should otherwise work
-transparently. :l
-
-Neighbor lists are constructed on the GPU. :l
-
-The package only supports use of a single MPI task, running on a
-single CPU (core), assigned to each GPU. :l,ule
-
-Here is a quick overview of how to use the USER-CUDA package:
-
-build the library in lib/cuda for your GPU hardware with desired precision
-include the USER-CUDA package and build LAMMPS
-use the mpirun command to specify 1 MPI task per GPU (on each node)
-enable the USER-CUDA package via the "-c on" command-line switch
-specify the # of GPUs per node
-use USER-CUDA styles in your input script :ul
-
-The latter two steps can be done using the "-pk cuda" and "-sf cuda"
-"command-line switches"_Section_start.html#start_7 respectively.  Or
-the effect of the "-pk" or "-sf" switches can be duplicated by adding
-the "package cuda"_package.html or "suffix cuda"_suffix.html commands
-respectively to your input script.
-
-[Required hardware/software:]
-
-To use this package, you need to have one or more NVIDIA GPUs and
-install the NVIDIA Cuda software on your system:
-
-Your NVIDIA GPU needs to support Compute Capability 1.3. This list may
-help you to find out the Compute Capability of your card:
-
-http://en.wikipedia.org/wiki/Comparison_of_Nvidia_graphics_processing_units
-
-Install the Nvidia Cuda Toolkit (version 3.2 or higher) and the
-corresponding GPU drivers.  The Nvidia Cuda SDK is not required, but
-we recommend it also be installed.  You can then make sure its sample
-projects can be compiled without problems.
-
-[Building LAMMPS with the USER-CUDA package:]
-
-This requires two steps (a,b): build the USER-CUDA library, then build
-LAMMPS with the USER-CUDA package.
-
-You can do both these steps in one line, using the src/Make.py script,
-described in "Section 2.4"_Section_start.html#start_4 of the manual.
-Type "Make.py -h" for help.  If run from the src directory, this
-command will create src/lmp_cuda using src/MAKE/Makefile.mpi as the
-starting Makefile.machine:
-
-Make.py -p cuda -cuda mode=single arch=20 -o cuda -a lib-cuda file mpi :pre
-
-Or you can follow these two (a,b) steps:
-
-(a) Build the USER-CUDA library
-
-The USER-CUDA library is in lammps/lib/cuda.  If your {CUDA} toolkit
-is not installed in the default system directoy {/usr/local/cuda} edit
-the file {lib/cuda/Makefile.common} accordingly.
-
-To build the library with the settings in lib/cuda/Makefile.default,
-simply type:
-
-make :pre
-
-To set options when the library is built, type "make OPTIONS", where
-{OPTIONS} are one or more of the following. The settings will be
-written to the {lib/cuda/Makefile.defaults} before the build.
-
-{precision=N} to set the precision level
-  N = 1 for single precision (default)
-  N = 2 for double precision
-  N = 3 for positions in double precision
-  N = 4 for positions and velocities in double precision
-{arch=M} to set GPU compute capability
-  M = 35 for Kepler GPUs
-  M = 20 for CC2.0 (GF100/110, e.g. C2050,GTX580,GTX470) (default)
-  M = 21 for CC2.1 (GF104/114,  e.g. GTX560, GTX460, GTX450)
-  M = 13 for CC1.3 (GF200, e.g. C1060, GTX285)
-{prec_timer=0/1} to use hi-precision timers
-  0 = do not use them (default)
-  1 = use them
-  this is usually only useful for Mac machines 
-{dbg=0/1} to activate debug mode
-  0 = no debug mode (default)
-  1 = yes debug mode
-  this is only useful for developers
-{cufft=1} for use of the CUDA FFT library
-  0 = no CUFFT support (default)
-  in the future other CUDA-enabled FFT libraries might be supported :pre
-
-If the build is successful, it will produce the files liblammpscuda.a and
-Makefile.lammps.
-
-Note that if you change any of the options (like precision), you need
-to re-build the entire library.  Do a "make clean" first, followed by
-"make".
-
-(b) Build LAMMPS with the USER-CUDA package
-
-cd lammps/src
-make yes-user-cuda
-make machine :pre
-
-No additional compile/link flags are needed in Makefile.machine.
-
-Note that if you change the USER-CUDA library precision (discussed
-above) and rebuild the USER-CUDA library, then you also need to
-re-install the USER-CUDA package and re-build LAMMPS, so that all
-affected files are re-compiled and linked to the new USER-CUDA
-library.
-
-[Run with the USER-CUDA package from the command line:]
-
-The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.
-
-When using the USER-CUDA package, you must use exactly one MPI task
-per physical GPU.
-
-You must use the "-c on" "command-line
-switch"_Section_start.html#start_7 to enable the USER-CUDA package.
-The "-c on" switch also issues a default "package cuda 1"_package.html
-command which sets various USER-CUDA options to default values, as
-discussed on the "package"_package.html command doc page.
-
-Use the "-sf cuda" "command-line switch"_Section_start.html#start_7,
-which will automatically append "cuda" to styles that support it.  Use
-the "-pk cuda Ng" "command-line switch"_Section_start.html#start_7 to
-set Ng = # of GPUs per node to a different value than the default set
-by the "-c on" switch (1 GPU) or change other "package
-cuda"_package.html options.
-
-lmp_machine -c on -sf cuda -pk cuda 1 -in in.script                       # 1 MPI task uses 1 GPU
-mpirun -np 2 lmp_machine -c on -sf cuda -pk cuda 2 -in in.script          # 2 MPI tasks use 2 GPUs on a single 16-core (or whatever) node
-mpirun -np 24 -ppn 2 lmp_machine -c on -sf cuda -pk cuda 2 -in in.script  # ditto on 12 16-core nodes :pre
-
-The syntax for the "-pk" switch is the same as same as the "package
-cuda" command.  See the "package"_package.html command doc page for
-details, including the default values used for all its options if it
-is not specified.
-
-Note that the default for the "package cuda"_package.html command is
-to set the Newton flag to "off" for both pairwise and bonded
-interactions.  This typically gives fastest performance.  If the
-"newton"_newton.html command is used in the input script, it can
-override these defaults.
-
-[Or run with the USER-CUDA package by editing an input script:]
-
-The discussion above for the mpirun/mpiexec command and the requirement
-of one MPI task per GPU is the same.
-
-You must still use the "-c on" "command-line
-switch"_Section_start.html#start_7 to enable the USER-CUDA package.
-
-Use the "suffix cuda"_suffix.html command, or you can explicitly add a
-"cuda" suffix to individual styles in your input script, e.g.
-
-pair_style lj/cut/cuda 2.5 :pre
-
-You only need to use the "package cuda"_package.html command if you
-wish to change any of its option defaults, including the number of
-GPUs/node (default = 1), as set by the "-c on" "command-line
-switch"_Section_start.html#start_7.
-
-[Speed-ups to expect:]
-
-The performance of a GPU versus a multi-core CPU is a function of your
-hardware, which pair style is used, the number of atoms/GPU, and the
-precision used on the GPU (double, single, mixed).
-
-See the "Benchmark page"_http://lammps.sandia.gov/bench.html of the
-LAMMPS web site for performance of the USER-CUDA package on different
-hardware.
-
-[Guidelines for best performance:]
-
-The USER-CUDA package offers more speed-up relative to CPU performance
-when the number of atoms per GPU is large, e.g. on the order of tens
-or hundreds of 1000s. :ulb,l
-
-As noted above, this package will continue to run a simulation
-entirely on the GPU(s) (except for inter-processor MPI communication),
-for multiple timesteps, until a CPU calculation is required, either by
-a fix or compute that is non-GPU-ized, or until output is performed
-(thermo or dump snapshot or restart file).  The less often this
-occurs, the faster your simulation will run. :l,ule
-
-[Restrictions:]
-
-None.

doc/accelerate_gpu.html

@@ -1,401 +0,0 @@
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-<li class="toctree-l1"><a class="reference internal" href="Section_intro.html">1. Introduction</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_start.html">2. Getting Started</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_commands.html">3. Commands</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="Section_python.html">11. Python interface to LAMMPS</a></li>
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-            
-  <p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
-<div class="section" id="gpu-package">
-<h1>5.GPU package<a class="headerlink" href="#gpu-package" title="Permalink to this headline">¶</a></h1>
-<p>The GPU package was developed by Mike Brown at ORNL and his
-collaborators, particularly Trung Nguyen (ORNL).  It provides GPU
-versions of many pair styles, including the 3-body Stillinger-Weber
-pair style, and for <a class="reference internal" href="kspace_style.html"><em>kspace_style pppm</em></a> for
-long-range Coulombics.  It has the following general features:</p>
-<ul class="simple">
-<li>It is designed to exploit common GPU hardware configurations where one
-or more GPUs are coupled to many cores of one or more multi-core CPUs,
-e.g. within a node of a parallel machine.</li>
-<li>Atom-based data (e.g. coordinates, forces) moves back-and-forth
-between the CPU(s) and GPU every timestep.</li>
-<li>Neighbor lists can be built on the CPU or on the GPU</li>
-<li>The charge assignement and force interpolation portions of PPPM can be
-run on the GPU.  The FFT portion, which requires MPI communication
-between processors, runs on the CPU.</li>
-<li>Asynchronous force computations can be performed simultaneously on the
-CPU(s) and GPU.</li>
-<li>It allows for GPU computations to be performed in single or double
-precision, or in mixed-mode precision, where pairwise forces are
-computed in single precision, but accumulated into double-precision
-force vectors.</li>
-<li>LAMMPS-specific code is in the GPU package.  It makes calls to a
-generic GPU library in the lib/gpu directory.  This library provides
-NVIDIA support as well as more general OpenCL support, so that the
-same functionality can eventually be supported on a variety of GPU
-hardware.</li>
-</ul>
-<p>Here is a quick overview of how to use the GPU package:</p>
-<ul class="simple">
-<li>build the library in lib/gpu for your GPU hardware wity desired precision</li>
-<li>include the GPU package and build LAMMPS</li>
-<li>use the mpirun command to set the number of MPI tasks/node which determines the number of MPI tasks/GPU</li>
-<li>specify the # of GPUs per node</li>
-<li>use GPU styles in your input script</li>
-</ul>
-<p>The latter two steps can be done using the &#8220;-pk gpu&#8221; and &#8220;-sf gpu&#8221;
-<a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> respectively.  Or
-the effect of the &#8220;-pk&#8221; or &#8220;-sf&#8221; switches can be duplicated by adding
-the <a class="reference internal" href="package.html"><em>package gpu</em></a> or <a class="reference internal" href="suffix.html"><em>suffix gpu</em></a> commands
-respectively to your input script.</p>
-<p><strong>Required hardware/software:</strong></p>
-<p>To use this package, you currently need to have an NVIDIA GPU and
-install the NVIDIA Cuda software on your system:</p>
-<ul class="simple">
-<li>Check if you have an NVIDIA GPU: cat /proc/driver/nvidia/gpus/0/information</li>
-<li>Go to <a class="reference external" href="http://www.nvidia.com/object/cuda_get.html">http://www.nvidia.com/object/cuda_get.html</a></li>
-<li>Install a driver and toolkit appropriate for your system (SDK is not necessary)</li>
-<li>Run lammps/lib/gpu/nvc_get_devices (after building the GPU library, see below) to list supported devices and properties</li>
-</ul>
-<p><strong>Building LAMMPS with the GPU package:</strong></p>
-<p>This requires two steps (a,b): build the GPU library, then build
-LAMMPS with the GPU package.</p>
-<p>You can do both these steps in one line, using the src/Make.py script,
-described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.
-Type &#8220;Make.py -h&#8221; for help.  If run from the src directory, this
-command will create src/lmp_gpu using src/MAKE/Makefile.mpi as the
-starting Makefile.machine:</p>
-<div class="highlight-python"><div class="highlight"><pre>Make.py -p gpu -gpu mode=single arch=31 -o gpu -a lib-gpu file mpi
-</pre></div>
-</div>
-<p>Or you can follow these two (a,b) steps:</p>
-<ol class="loweralpha simple">
-<li>Build the GPU library</li>
-</ol>
-<p>The GPU library is in lammps/lib/gpu.  Select a Makefile.machine (in
-lib/gpu) appropriate for your system.  You should pay special
-attention to 3 settings in this makefile.</p>
-<ul class="simple">
-<li>CUDA_HOME = needs to be where NVIDIA Cuda software is installed on your system</li>
-<li>CUDA_ARCH = needs to be appropriate to your GPUs</li>
-<li>CUDA_PREC = precision (double, mixed, single) you desire</li>
-</ul>
-<p>See lib/gpu/Makefile.linux.double for examples of the ARCH settings
-for different GPU choices, e.g. Fermi vs Kepler.  It also lists the
-possible precision settings:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">CUDA_PREC</span> <span class="o">=</span> <span class="o">-</span><span class="n">D_SINGLE_SINGLE</span>  <span class="c"># single precision for all calculations</span>
-<span class="n">CUDA_PREC</span> <span class="o">=</span> <span class="o">-</span><span class="n">D_DOUBLE_DOUBLE</span>  <span class="c"># double precision for all calculations</span>
-<span class="n">CUDA_PREC</span> <span class="o">=</span> <span class="o">-</span><span class="n">D_SINGLE_DOUBLE</span>  <span class="c"># accumulation of forces, etc, in double</span>
-</pre></div>
-</div>
-<p>The last setting is the mixed mode referred to above.  Note that your
-GPU must support double precision to use either the 2nd or 3rd of
-these settings.</p>
-<p>To build the library, type:</p>
-<div class="highlight-python"><div class="highlight"><pre>make -f Makefile.machine
-</pre></div>
-</div>
-<p>If successful, it will produce the files libgpu.a and Makefile.lammps.</p>
-<p>The latter file has 3 settings that need to be appropriate for the
-paths and settings for the CUDA system software on your machine.
-Makefile.lammps is a copy of the file specified by the EXTRAMAKE
-setting in Makefile.machine.  You can change EXTRAMAKE or create your
-own Makefile.lammps.machine if needed.</p>
-<p>Note that to change the precision of the GPU library, you need to
-re-build the entire library.  Do a &#8220;clean&#8221; first, e.g. &#8220;make -f
-Makefile.linux clean&#8221;, followed by the make command above.</p>
-<ol class="loweralpha simple" start="2">
-<li>Build LAMMPS with the GPU package</li>
-</ol>
-<div class="highlight-python"><div class="highlight"><pre>cd lammps/src
-make yes-gpu
-make machine
-</pre></div>
-</div>
-<p>No additional compile/link flags are needed in Makefile.machine.</p>
-<p>Note that if you change the GPU library precision (discussed above)
-and rebuild the GPU library, then you also need to re-install the GPU
-package and re-build LAMMPS, so that all affected files are
-re-compiled and linked to the new GPU library.</p>
-<p><strong>Run with the GPU package from the command line:</strong></p>
-<p>The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.</p>
-<p>When using the GPU package, you cannot assign more than one GPU to a
-single MPI task.  However multiple MPI tasks can share the same GPU,
-and in many cases it will be more efficient to run this way.  Likewise
-it may be more efficient to use less MPI tasks/node than the available
-# of CPU cores.  Assignment of multiple MPI tasks to a GPU will happen
-automatically if you create more MPI tasks/node than there are
-GPUs/mode.  E.g. with 8 MPI tasks/node and 2 GPUs, each GPU will be
-shared by 4 MPI tasks.</p>
-<p>Use the &#8220;-sf gpu&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>,
-which will automatically append &#8220;gpu&#8221; to styles that support it.  Use
-the &#8220;-pk gpu Ng&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to
-set Ng = # of GPUs/node to use.</p>
-<div class="highlight-python"><div class="highlight"><pre>lmp_machine -sf gpu -pk gpu 1 -in in.script                         # 1 MPI task uses 1 GPU
-mpirun -np 12 lmp_machine -sf gpu -pk gpu 2 -in in.script           # 12 MPI tasks share 2 GPUs on a single 16-core (or whatever) node
-mpirun -np 48 -ppn 12 lmp_machine -sf gpu -pk gpu 2 -in in.script   # ditto on 4 16-core nodes
-</pre></div>
-</div>
-<p>Note that if the &#8220;-sf gpu&#8221; switch is used, it also issues a default
-<a class="reference internal" href="package.html"><em>package gpu 1</em></a> command, which sets the number of
-GPUs/node to 1.</p>
-<p>Using the &#8220;-pk&#8221; switch explicitly allows for setting of the number of
-GPUs/node to use and additional options.  Its syntax is the same as
-same as the &#8220;package gpu&#8221; command.  See the <a class="reference internal" href="package.html"><em>package</em></a>
-command doc page for details, including the default values used for
-all its options if it is not specified.</p>
-<p>Note that the default for the <a class="reference internal" href="package.html"><em>package gpu</em></a> command is to
-set the Newton flag to &#8220;off&#8221; pairwise interactions.  It does not
-affect the setting for bonded interactions (LAMMPS default is &#8220;on&#8221;).
-The &#8220;off&#8221; setting for pairwise interaction is currently required for
-GPU package pair styles.</p>
-<p><strong>Or run with the GPU package by editing an input script:</strong></p>
-<p>The discussion above for the mpirun/mpiexec command, MPI tasks/node,
-and use of multiple MPI tasks/GPU is the same.</p>
-<p>Use the <a class="reference internal" href="suffix.html"><em>suffix gpu</em></a> command, or you can explicitly add an
-&#8220;gpu&#8221; suffix to individual styles in your input script, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/gpu 2.5
-</pre></div>
-</div>
-<p>You must also use the <a class="reference internal" href="package.html"><em>package gpu</em></a> command to enable the
-GPU package, unless the &#8220;-sf gpu&#8221; or &#8220;-pk gpu&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> were used.  It specifies the
-number of GPUs/node to use, as well as other options.</p>
-<p><strong>Speed-ups to expect:</strong></p>
-<p>The performance of a GPU versus a multi-core CPU is a function of your
-hardware, which pair style is used, the number of atoms/GPU, and the
-precision used on the GPU (double, single, mixed).</p>
-<p>See the <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the
-LAMMPS web site for performance of the GPU package on various
-hardware, including the Titan HPC platform at ORNL.</p>
-<p>You should also experiment with how many MPI tasks per GPU to use to
-give the best performance for your problem and machine.  This is also
-a function of the problem size and the pair style being using.
-Likewise, you should experiment with the precision setting for the GPU
-library to see if single or mixed precision will give accurate
-results, since they will typically be faster.</p>
-<p><strong>Guidelines for best performance:</strong></p>
-<ul class="simple">
-<li>Using multiple MPI tasks per GPU will often give the best performance,
-as allowed my most multi-core CPU/GPU configurations.</li>
-<li>If the number of particles per MPI task is small (e.g. 100s of
-particles), it can be more efficient to run with fewer MPI tasks per
-GPU, even if you do not use all the cores on the compute node.</li>
-<li>The <a class="reference internal" href="package.html"><em>package gpu</em></a> command has several options for tuning
-performance.  Neighbor lists can be built on the GPU or CPU.  Force
-calculations can be dynamically balanced across the CPU cores and
-GPUs.  GPU-specific settings can be made which can be optimized
-for different hardware.  See the <a class="reference internal" href="package.html"><em>packakge</em></a> command
-doc page for details.</li>
-<li>As described by the <a class="reference internal" href="package.html"><em>package gpu</em></a> command, GPU
-accelerated pair styles can perform computations asynchronously with
-CPU computations. The &#8220;Pair&#8221; time reported by LAMMPS will be the
-maximum of the time required to complete the CPU pair style
-computations and the time required to complete the GPU pair style
-computations. Any time spent for GPU-enabled pair styles for
-computations that run simultaneously with <a class="reference internal" href="bond_style.html"><em>bond</em></a>,
-<a class="reference internal" href="angle_style.html"><em>angle</em></a>, <a class="reference internal" href="dihedral_style.html"><em>dihedral</em></a>,
-<a class="reference internal" href="improper_style.html"><em>improper</em></a>, and <a class="reference internal" href="kspace_style.html"><em>long-range</em></a>
-calculations will not be included in the &#8220;Pair&#8221; time.</li>
-<li>When the <em>mode</em> setting for the package gpu command is force/neigh,
-the time for neighbor list calculations on the GPU will be added into
-the &#8220;Pair&#8221; time, not the &#8220;Neigh&#8221; time.  An additional breakdown of the
-times required for various tasks on the GPU (data copy, neighbor
-calculations, force computations, etc) are output only with the LAMMPS
-screen output (not in the log file) at the end of each run.  These
-timings represent total time spent on the GPU for each routine,
-regardless of asynchronous CPU calculations.</li>
-<li>The output section &#8220;GPU Time Info (average)&#8221; reports &#8220;Max Mem / Proc&#8221;.
-This is the maximum memory used at one time on the GPU for data
-storage by a single MPI process.</li>
-</ul>
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>None.</p>
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-  <p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
-<div class="section" id="user-intel-package">
-<h1>5.USER-INTEL package<a class="headerlink" href="#user-intel-package" title="Permalink to this headline">¶</a></h1>
-<p>The USER-INTEL package was developed by Mike Brown at Intel
-Corporation.  It provides two methods for accelerating simulations,
-depending on the hardware you have.  The first is acceleration on
-Intel(R) CPUs by running in single, mixed, or double precision with
-vectorization.  The second is acceleration on Intel(R) Xeon Phi(TM)
-coprocessors via offloading neighbor list and non-bonded force
-calculations to the Phi.  The same C++ code is used in both cases.
-When offloading to a coprocessor from a CPU, the same routine is run
-twice, once on the CPU and once with an offload flag.</p>
-<p>Note that the USER-INTEL package supports use of the Phi in &#8220;offload&#8221;
-mode, not &#8220;native&#8221; mode like the <a class="reference internal" href="accelerate_kokkos.html"><em>KOKKOS package</em></a>.</p>
-<p>Also note that the USER-INTEL package can be used in tandem with the
-<a class="reference internal" href="accelerate_omp.html"><em>USER-OMP package</em></a>.  This is useful when
-offloading pair style computations to the Phi, so that other styles
-not supported by the USER-INTEL package, e.g. bond, angle, dihedral,
-improper, and long-range electrostatics, can run simultaneously in
-threaded mode on the CPU cores.  Since less MPI tasks than CPU cores
-will typically be invoked when running with coprocessors, this enables
-the extra CPU cores to be used for useful computation.</p>
-<p>As illustrated below, if LAMMPS is built with both the USER-INTEL and
-USER-OMP packages, this dual mode of operation is made easier to use,
-via the &#8220;-suffix hybrid intel omp&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> or the <a class="reference internal" href="suffix.html"><em>suffix hybrid intel omp</em></a> command.  Both set a second-choice suffix to &#8220;omp&#8221; so
-that styles from the USER-INTEL package will be used if available,
-with styles from the USER-OMP package as a second choice.</p>
-<p>Here is a quick overview of how to use the USER-INTEL package for CPU
-acceleration, assuming one or more 16-core nodes.  More details
-follow.</p>
-<div class="highlight-python"><div class="highlight"><pre>use an Intel compiler
-use these CCFLAGS settings in Makefile.machine: -fopenmp, -DLAMMPS_MEMALIGN=64, -restrict, -xHost, -fno-alias, -ansi-alias, -override-limits
-use these LINKFLAGS settings in Makefile.machine: -fopenmp, -xHost
-make yes-user-intel yes-user-omp     # including user-omp is optional
-make mpi                             # build with the USER-INTEL package, if settings (including compiler) added to Makefile.mpi
-make intel_cpu                       # or Makefile.intel_cpu already has settings, uses Intel MPI wrapper
-Make.py -v -p intel omp -intel cpu -a file mpich_icc   # or one-line build via Make.py for MPICH
-Make.py -v -p intel omp -intel cpu -a file ompi_icc    # or for OpenMPI
-Make.py -v -p intel omp -intel cpu -a file intel_cpu   # or for Intel MPI wrapper
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre>lmp_machine -sf intel -pk intel 0 omp 16 -in in.script    # 1 node, 1 MPI task/node, 16 threads/task, no USER-OMP
-mpirun -np 32 lmp_machine -sf intel -in in.script         # 2 nodess, 16 MPI tasks/node, no threads, no USER-OMP
-lmp_machine -sf hybrid intel omp -pk intel 0 omp 16 -pk omp 16 -in in.script         # 1 node, 1 MPI task/node, 16 threads/task, with USER-OMP
-mpirun -np 32 -ppn 4 lmp_machine -sf hybrid intel omp -pk omp 4 -pk omp 4 -in in.script      # 8 nodes, 4 MPI tasks/node, 4 threads/task, with USER-OMP
-</pre></div>
-</div>
-<p>Here is a quick overview of how to use the USER-INTEL package for the
-same CPUs as above (16 cores/node), with an additional Xeon Phi(TM)
-coprocessor per node.  More details follow.</p>
-<div class="highlight-python"><div class="highlight"><pre>Same as above for building, with these additions/changes:
-add the flag -DLMP_INTEL_OFFLOAD to CCFLAGS in Makefile.machine
-add the flag -offload to LINKFLAGS in Makefile.machine
-for Make.py change &quot;-intel cpu&quot; to &quot;-intel phi&quot;, and &quot;file intel_cpu&quot; to &quot;file intel_phi&quot;
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre>mpirun -np 32 lmp_machine -sf intel -pk intel 1 -in in.script                 # 2 nodes, 16 MPI tasks/node, 240 total threads on coprocessor, no USER-OMP
-mpirun -np 16 -ppn 8 lmp_machine -sf intel -pk intel 1 omp 2 -in in.script            # 2 nodes, 8 MPI tasks/node, 2 threads/task, 240 total threads on coprocessor, no USER-OMP
-mpirun -np 32 -ppn 8 lmp_machine -sf hybrid intel omp -pk intel 1 omp 2 -pk omp 2 -in in.script # 4 nodes, 8 MPI tasks/node, 2 threads/task, 240 total threads on coprocessor, with USER-OMP
-</pre></div>
-</div>
-<p><strong>Required hardware/software:</strong></p>
-<p>Your compiler must support the OpenMP interface.  Use of an Intel(R)
-C++ compiler is recommended, but not required.  However, g++ will not
-recognize some of the settings listed above, so they cannot be used.
-Optimizations for vectorization have only been tested with the
-Intel(R) compiler.  Use of other compilers may not result in
-vectorization, or give poor performance.</p>
-<p>The recommended version of the Intel(R) compiler is 14.0.1.106.
-Versions 15.0.1.133 and later are also supported.  If using Intel(R)
-MPI, versions 15.0.2.044 and later are recommended.</p>
-<p>To use the offload option, you must have one or more Intel(R) Xeon
-Phi(TM) coprocessors and use an Intel(R) C++ compiler.</p>
-<p><strong>Building LAMMPS with the USER-INTEL package:</strong></p>
-<p>The lines above illustrate how to include/build with the USER-INTEL
-package, for either CPU or Phi support, in two steps, using the &#8220;make&#8221;
-command.  Or how to do it with one command via the src/Make.py script,
-described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.
-Type &#8220;Make.py -h&#8221; for help.  Because the mechanism for specifing what
-compiler to use (Intel in this case) is different for different MPI
-wrappers, 3 versions of the Make.py command are shown.</p>
-<p>Note that if you build with support for a Phi coprocessor, the same
-binary can be used on nodes with or without coprocessors installed.
-However, if you do not have coprocessors on your system, building
-without offload support will produce a smaller binary.</p>
-<p>If you also build with the USER-OMP package, you can use styles from
-both packages, as described below.</p>
-<p>Note that the CCFLAGS and LINKFLAGS settings in Makefile.machine must
-include &#8220;-fopenmp&#8221;.  Likewise, if you use an Intel compiler, the
-CCFLAGS setting must include &#8220;-restrict&#8221;.  For Phi support, the
-&#8220;-DLMP_INTEL_OFFLOAD&#8221; (CCFLAGS) and &#8220;-offload&#8221; (LINKFLAGS) settings
-are required.  The other settings listed above are optional, but will
-typically improve performance.  The Make.py command will add all of
-these automatically.</p>
-<p>If you are compiling on the same architecture that will be used for
-the runs, adding the flag <em>-xHost</em> to CCFLAGS enables vectorization
-with the Intel(R) compiler.  Otherwise, you must provide the correct
-compute node architecture to the -x option (e.g. -xAVX).</p>
-<p>Example machines makefiles Makefile.intel_cpu and Makefile.intel_phi
-are included in the src/MAKE/OPTIONS directory with settings that
-perform well with the Intel(R) compiler. The latter has support for
-offload to Phi coprocessors; the former does not.</p>
-<p><strong>Run with the USER-INTEL package from the command line:</strong></p>
-<p>The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.</p>
-<p>If you compute (any portion of) pairwise interactions using USER-INTEL
-pair styles on the CPU, or use USER-OMP styles on the CPU, you need to
-choose how many OpenMP threads per MPI task to use.  If both packages
-are used, it must be done for both packages, and the same thread count
-value should be used for both.  Note that the product of MPI tasks *
-threads/task should not exceed the physical number of cores (on a
-node), otherwise performance will suffer.</p>
-<p>When using the USER-INTEL package for the Phi, you also need to
-specify the number of coprocessor/node and optionally the number of
-coprocessor threads per MPI task to use.  Note that coprocessor
-threads (which run on the coprocessor) are totally independent from
-OpenMP threads (which run on the CPU).  The default values for the
-settings that affect coprocessor threads are typically fine, as
-discussed below.</p>
-<p>As in the lines above, use the &#8220;-sf intel&#8221; or &#8220;-sf hybrid intel omp&#8221;
-<a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>, which will
-automatically append &#8220;intel&#8221; to styles that support it.  In the second
-case, &#8220;omp&#8221; will be appended if an &#8220;intel&#8221; style does not exist.</p>
-<p>Note that if either switch is used, it also invokes a default command:
-<a class="reference internal" href="package.html"><em>package intel 1</em></a>.  If the &#8220;-sf hybrid intel omp&#8221; switch
-is used, the default USER-OMP command <a class="reference internal" href="package.html"><em>package omp 0</em></a> is
-also invoked (if LAMMPS was built with USER-OMP).  Both set the number
-of OpenMP threads per MPI task via the OMP_NUM_THREADS environment
-variable.  The first command sets the number of Xeon Phi(TM)
-coprocessors/node to 1 (ignored if USER-INTEL is built for CPU-only),
-and the precision mode to &#8220;mixed&#8221; (default value).</p>
-<p>You can also use the &#8220;-pk intel Nphi&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to explicitly set Nphi = # of Xeon
-Phi(TM) coprocessors/node, as well as additional options.  Nphi should
-be &gt;= 1 if LAMMPS was built with coprocessor support, otherswise Nphi
-= 0 for a CPU-only build.  All the available coprocessor threads on
-each Phi will be divided among MPI tasks, unless the <em>tptask</em> option
-of the &#8220;-pk intel&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> is
-used to limit the coprocessor threads per MPI task.  See the <a class="reference internal" href="package.html"><em>package intel</em></a> command for details, including the default values
-used for all its options if not specified, and how to set the number
-of OpenMP threads via the OMP_NUM_THREADS environment variable if
-desired.</p>
-<p>If LAMMPS was built with the USER-OMP package, you can also use the
-&#8220;-pk omp Nt&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to
-explicitly set Nt = # of OpenMP threads per MPI task to use, as well
-as additional options.  Nt should be the same threads per MPI task as
-set for the USER-INTEL package, e.g. via the &#8220;-pk intel Nphi omp Nt&#8221;
-command.  Again, see the <a class="reference internal" href="package.html"><em>package omp</em></a> command for
-details, including the default values used for all its options if not
-specified, and how to set the number of OpenMP threads via the
-OMP_NUM_THREADS environment variable if desired.</p>
-<p><strong>Or run with the USER-INTEL package by editing an input script:</strong></p>
-<p>The discussion above for the mpirun/mpiexec command, MPI tasks/node,
-OpenMP threads per MPI task, and coprocessor threads per MPI task is
-the same.</p>
-<p>Use the <a class="reference internal" href="suffix.html"><em>suffix intel</em></a> or <a class="reference internal" href="suffix.html"><em>suffix hybrid intel omp</em></a> commands, or you can explicitly add an &#8220;intel&#8221; or
-&#8220;omp&#8221; suffix to individual styles in your input script, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/intel 2.5
-</pre></div>
-</div>
-<p>You must also use the <a class="reference internal" href="package.html"><em>package intel</em></a> command, unless the
-&#8220;-sf intel&#8221; or &#8220;-pk intel&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> were used.  It specifies how many
-coprocessors/node to use, as well as other OpenMP threading and
-coprocessor options.  The <a class="reference internal" href="package.html"><em>package</em></a> doc page explains how
-to set the number of OpenMP threads via an environment variable if
-desired.</p>
-<p>If LAMMPS was also built with the USER-OMP package, you must also use
-the <a class="reference internal" href="package.html"><em>package omp</em></a> command to enable that package, unless
-the &#8220;-sf hybrid intel omp&#8221; or &#8220;-pk omp&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a> were used.  It specifies how many
-OpenMP threads per MPI task to use (should be same as the setting for
-the USER-INTEL package), as well as other options.  Its doc page
-explains how to set the number of OpenMP threads via an environment
-variable if desired.</p>
-<p><strong>Speed-ups to expect:</strong></p>
-<p>If LAMMPS was not built with coprocessor support (CPU only) when
-including the USER-INTEL package, then acclerated styles will run on
-the CPU using vectorization optimizations and the specified precision.
-This may give a substantial speed-up for a pair style, particularly if
-mixed or single precision is used.</p>
-<p>If LAMMPS was built with coproccesor support, the pair styles will run
-on one or more Intel(R) Xeon Phi(TM) coprocessors (per node).  The
-performance of a Xeon Phi versus a multi-core CPU is a function of
-your hardware, which pair style is used, the number of
-atoms/coprocessor, and the precision used on the coprocessor (double,
-single, mixed).</p>
-<p>See the <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the
-LAMMPS web site for performance of the USER-INTEL package on different
-hardware.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">Setting core affinity is often used to pin MPI tasks
-and OpenMP threads to a core or group of cores so that memory access
-can be uniform. Unless disabled at build time, affinity for MPI tasks
-and OpenMP threads on the host (CPU) will be set by default on the
-host when using offload to a coprocessor. In this case, it is
-unnecessary to use other methods to control affinity (e.g. taskset,
-numactl, I_MPI_PIN_DOMAIN, etc.). This can be disabled in an input
-script with the <em>no_affinity</em> option to the <a class="reference internal" href="package.html"><em>package intel</em></a> command or by disabling the option at build time
-(by adding -DINTEL_OFFLOAD_NOAFFINITY to the CCFLAGS line of your
-Makefile).  Disabling this option is not recommended, especially when
-running on a machine with hyperthreading disabled.</p>
-</div>
-<p><strong>Guidelines for best performance on an Intel(R) Xeon Phi(TM)
-coprocessor:</strong></p>
-<ul class="simple">
-<li>The default for the <a class="reference internal" href="package.html"><em>package intel</em></a> command is to have
-all the MPI tasks on a given compute node use a single Xeon Phi(TM)
-coprocessor.  In general, running with a large number of MPI tasks on
-each node will perform best with offload.  Each MPI task will
-automatically get affinity to a subset of the hardware threads
-available on the coprocessor.  For example, if your card has 61 cores,
-with 60 cores available for offload and 4 hardware threads per core
-(240 total threads), running with 24 MPI tasks per node will cause
-each MPI task to use a subset of 10 threads on the coprocessor.  Fine
-tuning of the number of threads to use per MPI task or the number of
-threads to use per core can be accomplished with keyword settings of
-the <a class="reference internal" href="package.html"><em>package intel</em></a> command.</li>
-<li>If desired, only a fraction of the pair style computation can be
-offloaded to the coprocessors.  This is accomplished by using the
-<em>balance</em> keyword in the <a class="reference internal" href="package.html"><em>package intel</em></a> command.  A
-balance of 0 runs all calculations on the CPU.  A balance of 1 runs
-all calculations on the coprocessor.  A balance of 0.5 runs half of
-the calculations on the coprocessor.  Setting the balance to -1 (the
-default) will enable dynamic load balancing that continously adjusts
-the fraction of offloaded work throughout the simulation.  This option
-typically produces results within 5 to 10 percent of the optimal fixed
-balance.</li>
-<li>When using offload with CPU hyperthreading disabled, it may help
-performance to use fewer MPI tasks and OpenMP threads than available
-cores.  This is due to the fact that additional threads are generated
-internally to handle the asynchronous offload tasks.</li>
-<li>If running short benchmark runs with dynamic load balancing, adding a
-short warm-up run (10-20 steps) will allow the load-balancer to find a
-near-optimal setting that will carry over to additional runs.</li>
-<li>If pair computations are being offloaded to an Intel(R) Xeon Phi(TM)
-coprocessor, a diagnostic line is printed to the screen (not to the
-log file), during the setup phase of a run, indicating that offload
-mode is being used and indicating the number of coprocessor threads
-per MPI task.  Additionally, an offload timing summary is printed at
-the end of each run.  When offloading, the frequency for <a class="reference internal" href="atom_modify.html"><em>atom sorting</em></a> is changed to 1 so that the per-atom data is
-effectively sorted at every rebuild of the neighbor lists.</li>
-<li>For simulations with long-range electrostatics or bond, angle,
-dihedral, improper calculations, computation and data transfer to the
-coprocessor will run concurrently with computations and MPI
-communications for these calculations on the host CPU.  The USER-INTEL
-package has two modes for deciding which atoms will be handled by the
-coprocessor.  This choice is controlled with the <em>ghost</em> keyword of
-the <a class="reference internal" href="package.html"><em>package intel</em></a> command.  When set to 0, ghost atoms
-(atoms at the borders between MPI tasks) are not offloaded to the
-card.  This allows for overlap of MPI communication of forces with
-computation on the coprocessor when the <a class="reference internal" href="newton.html"><em>newton</em></a> setting
-is &#8220;on&#8221;.  The default is dependent on the style being used, however,
-better performance may be achieved by setting this option
-explictly.</li>
-</ul>
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>When offloading to a coprocessor, <a class="reference internal" href="pair_hybrid.html"><em>hybrid</em></a> styles
-that require skip lists for neighbor builds cannot be offloaded.
-Using <a class="reference internal" href="pair_hybrid.html"><em>hybrid/overlay</em></a> is allowed.  Only one intel
-accelerated style may be used with hybrid styles.
-<a class="reference internal" href="special_bonds.html"><em>Special_bonds</em></a> exclusion lists are not currently
-supported with offload, however, the same effect can often be
-accomplished by setting cutoffs for excluded atom types to 0.  None of
-the pair styles in the USER-INTEL package currently support the
-&#8220;inner&#8221;, &#8220;middle&#8221;, &#8220;outer&#8221; options for rRESPA integration via the
-<a class="reference internal" href="run_style.html"><em>run_style respa</em></a> command; only the &#8220;pair&#8221; option is
-supported.</p>
-</div>
-</div>
-
-
-           </div>
-          </div>
-          <footer>
-  
-
-  <hr/>
-
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doc/accelerate_intel.txt

@@ -1,321 +0,0 @@
-"Previous Section"_Section_packages.html - "LAMMPS WWW Site"_lws -
-"LAMMPS Documentation"_ld - "LAMMPS Commands"_lc :c
-
-:link(lws,http://lammps.sandia.gov)
-:link(ld,Manual.html)
-:link(lc,Section_commands.html#comm)
-
-:line
-
-"Return to Section accelerate overview"_Section_accelerate.html
-
-5.3.3 USER-INTEL package :h4
-
-The USER-INTEL package was developed by Mike Brown at Intel
-Corporation.  It provides two methods for accelerating simulations,
-depending on the hardware you have.  The first is acceleration on
-Intel(R) CPUs by running in single, mixed, or double precision with
-vectorization.  The second is acceleration on Intel(R) Xeon Phi(TM)
-coprocessors via offloading neighbor list and non-bonded force
-calculations to the Phi.  The same C++ code is used in both cases.
-When offloading to a coprocessor from a CPU, the same routine is run
-twice, once on the CPU and once with an offload flag.
-
-Note that the USER-INTEL package supports use of the Phi in "offload"
-mode, not "native" mode like the "KOKKOS
-package"_accelerate_kokkos.html.
-
-Also note that the USER-INTEL package can be used in tandem with the
-"USER-OMP package"_accelerate_omp.html.  This is useful when
-offloading pair style computations to the Phi, so that other styles
-not supported by the USER-INTEL package, e.g. bond, angle, dihedral,
-improper, and long-range electrostatics, can run simultaneously in
-threaded mode on the CPU cores.  Since less MPI tasks than CPU cores
-will typically be invoked when running with coprocessors, this enables
-the extra CPU cores to be used for useful computation.
-
-As illustrated below, if LAMMPS is built with both the USER-INTEL and
-USER-OMP packages, this dual mode of operation is made easier to use,
-via the "-suffix hybrid intel omp" "command-line
-switch"_Section_start.html#start_7 or the "suffix hybrid intel
-omp"_suffix.html command.  Both set a second-choice suffix to "omp" so
-that styles from the USER-INTEL package will be used if available,
-with styles from the USER-OMP package as a second choice.
-
-Here is a quick overview of how to use the USER-INTEL package for CPU
-acceleration, assuming one or more 16-core nodes.  More details
-follow.
-
-use an Intel compiler
-use these CCFLAGS settings in Makefile.machine: -fopenmp, -DLAMMPS_MEMALIGN=64, -restrict, -xHost, -fno-alias, -ansi-alias, -override-limits
-use these LINKFLAGS settings in Makefile.machine: -fopenmp, -xHost
-make yes-user-intel yes-user-omp     # including user-omp is optional
-make mpi                             # build with the USER-INTEL package, if settings (including compiler) added to Makefile.mpi
-make intel_cpu                       # or Makefile.intel_cpu already has settings, uses Intel MPI wrapper
-Make.py -v -p intel omp -intel cpu -a file mpich_icc   # or one-line build via Make.py for MPICH
-Make.py -v -p intel omp -intel cpu -a file ompi_icc    # or for OpenMPI
-Make.py -v -p intel omp -intel cpu -a file intel_cpu   # or for Intel MPI wrapper :pre
-
-lmp_machine -sf intel -pk intel 0 omp 16 -in in.script    # 1 node, 1 MPI task/node, 16 threads/task, no USER-OMP
-mpirun -np 32 lmp_machine -sf intel -in in.script         # 2 nodess, 16 MPI tasks/node, no threads, no USER-OMP
-lmp_machine -sf hybrid intel omp -pk intel 0 omp 16 -pk omp 16 -in in.script         # 1 node, 1 MPI task/node, 16 threads/task, with USER-OMP
-mpirun -np 32 -ppn 4 lmp_machine -sf hybrid intel omp -pk omp 4 -pk omp 4 -in in.script      # 8 nodes, 4 MPI tasks/node, 4 threads/task, with USER-OMP :pre
-
-Here is a quick overview of how to use the USER-INTEL package for the
-same CPUs as above (16 cores/node), with an additional Xeon Phi(TM)
-coprocessor per node.  More details follow.
-
-Same as above for building, with these additions/changes:
-add the flag -DLMP_INTEL_OFFLOAD to CCFLAGS in Makefile.machine
-add the flag -offload to LINKFLAGS in Makefile.machine
-for Make.py change "-intel cpu" to "-intel phi", and "file intel_cpu" to "file intel_phi" :pre
-
-mpirun -np 32 lmp_machine -sf intel -pk intel 1 -in in.script                 # 2 nodes, 16 MPI tasks/node, 240 total threads on coprocessor, no USER-OMP
-mpirun -np 16 -ppn 8 lmp_machine -sf intel -pk intel 1 omp 2 -in in.script            # 2 nodes, 8 MPI tasks/node, 2 threads/task, 240 total threads on coprocessor, no USER-OMP
-mpirun -np 32 -ppn 8 lmp_machine -sf hybrid intel omp -pk intel 1 omp 2 -pk omp 2 -in in.script # 4 nodes, 8 MPI tasks/node, 2 threads/task, 240 total threads on coprocessor, with USER-OMP :pre
-
-[Required hardware/software:]
-
-Your compiler must support the OpenMP interface.  Use of an Intel(R)
-C++ compiler is recommended, but not required.  However, g++ will not
-recognize some of the settings listed above, so they cannot be used.
-Optimizations for vectorization have only been tested with the
-Intel(R) compiler.  Use of other compilers may not result in
-vectorization, or give poor performance.
-
-The recommended version of the Intel(R) compiler is 14.0.1.106. 
-Versions 15.0.1.133 and later are also supported.  If using Intel(R) 
-MPI, versions 15.0.2.044 and later are recommended.
-
-To use the offload option, you must have one or more Intel(R) Xeon
-Phi(TM) coprocessors and use an Intel(R) C++ compiler.  
-
-[Building LAMMPS with the USER-INTEL package:]
-
-The lines above illustrate how to include/build with the USER-INTEL
-package, for either CPU or Phi support, in two steps, using the "make"
-command.  Or how to do it with one command via the src/Make.py script,
-described in "Section 2.4"_Section_start.html#start_4 of the manual.
-Type "Make.py -h" for help.  Because the mechanism for specifing what
-compiler to use (Intel in this case) is different for different MPI
-wrappers, 3 versions of the Make.py command are shown.
-
-Note that if you build with support for a Phi coprocessor, the same
-binary can be used on nodes with or without coprocessors installed.
-However, if you do not have coprocessors on your system, building
-without offload support will produce a smaller binary.
-
-If you also build with the USER-OMP package, you can use styles from
-both packages, as described below.
-
-Note that the CCFLAGS and LINKFLAGS settings in Makefile.machine must
-include "-fopenmp".  Likewise, if you use an Intel compiler, the
-CCFLAGS setting must include "-restrict".  For Phi support, the
-"-DLMP_INTEL_OFFLOAD" (CCFLAGS) and "-offload" (LINKFLAGS) settings
-are required.  The other settings listed above are optional, but will
-typically improve performance.  The Make.py command will add all of
-these automatically.
-
-If you are compiling on the same architecture that will be used for
-the runs, adding the flag {-xHost} to CCFLAGS enables vectorization
-with the Intel(R) compiler.  Otherwise, you must provide the correct
-compute node architecture to the -x option (e.g. -xAVX).
-
-Example machines makefiles Makefile.intel_cpu and Makefile.intel_phi
-are included in the src/MAKE/OPTIONS directory with settings that
-perform well with the Intel(R) compiler. The latter has support for
-offload to Phi coprocessors; the former does not.
-
-[Run with the USER-INTEL package from the command line:]
-
-The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.
-
-If you compute (any portion of) pairwise interactions using USER-INTEL
-pair styles on the CPU, or use USER-OMP styles on the CPU, you need to
-choose how many OpenMP threads per MPI task to use.  If both packages
-are used, it must be done for both packages, and the same thread count
-value should be used for both.  Note that the product of MPI tasks *
-threads/task should not exceed the physical number of cores (on a
-node), otherwise performance will suffer.
-
-When using the USER-INTEL package for the Phi, you also need to
-specify the number of coprocessor/node and optionally the number of
-coprocessor threads per MPI task to use.  Note that coprocessor
-threads (which run on the coprocessor) are totally independent from
-OpenMP threads (which run on the CPU).  The default values for the
-settings that affect coprocessor threads are typically fine, as
-discussed below.
-
-As in the lines above, use the "-sf intel" or "-sf hybrid intel omp"
-"command-line switch"_Section_start.html#start_7, which will
-automatically append "intel" to styles that support it.  In the second
-case, "omp" will be appended if an "intel" style does not exist.
-
-Note that if either switch is used, it also invokes a default command:
-"package intel 1"_package.html.  If the "-sf hybrid intel omp" switch
-is used, the default USER-OMP command "package omp 0"_package.html is
-also invoked (if LAMMPS was built with USER-OMP).  Both set the number
-of OpenMP threads per MPI task via the OMP_NUM_THREADS environment
-variable.  The first command sets the number of Xeon Phi(TM)
-coprocessors/node to 1 (ignored if USER-INTEL is built for CPU-only),
-and the precision mode to "mixed" (default value).
-
-You can also use the "-pk intel Nphi" "command-line
-switch"_Section_start.html#start_7 to explicitly set Nphi = # of Xeon
-Phi(TM) coprocessors/node, as well as additional options.  Nphi should
-be >= 1 if LAMMPS was built with coprocessor support, otherswise Nphi
-= 0 for a CPU-only build.  All the available coprocessor threads on
-each Phi will be divided among MPI tasks, unless the {tptask} option
-of the "-pk intel" "command-line switch"_Section_start.html#start_7 is
-used to limit the coprocessor threads per MPI task.  See the "package
-intel"_package.html command for details, including the default values
-used for all its options if not specified, and how to set the number
-of OpenMP threads via the OMP_NUM_THREADS environment variable if
-desired.
-
-If LAMMPS was built with the USER-OMP package, you can also use the
-"-pk omp Nt" "command-line switch"_Section_start.html#start_7 to
-explicitly set Nt = # of OpenMP threads per MPI task to use, as well
-as additional options.  Nt should be the same threads per MPI task as
-set for the USER-INTEL package, e.g. via the "-pk intel Nphi omp Nt"
-command.  Again, see the "package omp"_package.html command for
-details, including the default values used for all its options if not
-specified, and how to set the number of OpenMP threads via the
-OMP_NUM_THREADS environment variable if desired.
-
-[Or run with the USER-INTEL package by editing an input script:]
-
-The discussion above for the mpirun/mpiexec command, MPI tasks/node,
-OpenMP threads per MPI task, and coprocessor threads per MPI task is
-the same.
-
-Use the "suffix intel"_suffix.html or "suffix hybrid intel
-omp"_suffix.html commands, or you can explicitly add an "intel" or
-"omp" suffix to individual styles in your input script, e.g.
-
-pair_style lj/cut/intel 2.5 :pre
-
-You must also use the "package intel"_package.html command, unless the
-"-sf intel" or "-pk intel" "command-line
-switches"_Section_start.html#start_7 were used.  It specifies how many
-coprocessors/node to use, as well as other OpenMP threading and
-coprocessor options.  The "package"_package.html doc page explains how
-to set the number of OpenMP threads via an environment variable if
-desired.
-
-If LAMMPS was also built with the USER-OMP package, you must also use
-the "package omp"_package.html command to enable that package, unless
-the "-sf hybrid intel omp" or "-pk omp" "command-line
-switches"_Section_start.html#start_7 were used.  It specifies how many
-OpenMP threads per MPI task to use (should be same as the setting for
-the USER-INTEL package), as well as other options.  Its doc page
-explains how to set the number of OpenMP threads via an environment
-variable if desired.
-
-[Speed-ups to expect:]
-
-If LAMMPS was not built with coprocessor support (CPU only) when
-including the USER-INTEL package, then acclerated styles will run on
-the CPU using vectorization optimizations and the specified precision.
-This may give a substantial speed-up for a pair style, particularly if
-mixed or single precision is used.
-
-If LAMMPS was built with coproccesor support, the pair styles will run
-on one or more Intel(R) Xeon Phi(TM) coprocessors (per node).  The
-performance of a Xeon Phi versus a multi-core CPU is a function of
-your hardware, which pair style is used, the number of
-atoms/coprocessor, and the precision used on the coprocessor (double,
-single, mixed).
-
-See the "Benchmark page"_http://lammps.sandia.gov/bench.html of the
-LAMMPS web site for performance of the USER-INTEL package on different
-hardware.
-
-IMPORTANT NOTE: Setting core affinity is often used to pin MPI tasks
-and OpenMP threads to a core or group of cores so that memory access
-can be uniform. Unless disabled at build time, affinity for MPI tasks
-and OpenMP threads on the host (CPU) will be set by default on the
-host when using offload to a coprocessor. In this case, it is
-unnecessary to use other methods to control affinity (e.g. taskset,
-numactl, I_MPI_PIN_DOMAIN, etc.). This can be disabled in an input
-script with the {no_affinity} option to the "package
-intel"_package.html command or by disabling the option at build time
-(by adding -DINTEL_OFFLOAD_NOAFFINITY to the CCFLAGS line of your
-Makefile).  Disabling this option is not recommended, especially when
-running on a machine with hyperthreading disabled.
-
-[Guidelines for best performance on an Intel(R) Xeon Phi(TM)
-coprocessor:]
-
-The default for the "package intel"_package.html command is to have
-all the MPI tasks on a given compute node use a single Xeon Phi(TM)
-coprocessor.  In general, running with a large number of MPI tasks on
-each node will perform best with offload.  Each MPI task will
-automatically get affinity to a subset of the hardware threads
-available on the coprocessor.  For example, if your card has 61 cores,
-with 60 cores available for offload and 4 hardware threads per core
-(240 total threads), running with 24 MPI tasks per node will cause
-each MPI task to use a subset of 10 threads on the coprocessor.  Fine
-tuning of the number of threads to use per MPI task or the number of
-threads to use per core can be accomplished with keyword settings of
-the "package intel"_package.html command. :ulb,l
-
-If desired, only a fraction of the pair style computation can be
-offloaded to the coprocessors.  This is accomplished by using the
-{balance} keyword in the "package intel"_package.html command.  A
-balance of 0 runs all calculations on the CPU.  A balance of 1 runs
-all calculations on the coprocessor.  A balance of 0.5 runs half of
-the calculations on the coprocessor.  Setting the balance to -1 (the
-default) will enable dynamic load balancing that continously adjusts
-the fraction of offloaded work throughout the simulation.  This option
-typically produces results within 5 to 10 percent of the optimal fixed
-balance. :l
-
-When using offload with CPU hyperthreading disabled, it may help
-performance to use fewer MPI tasks and OpenMP threads than available
-cores.  This is due to the fact that additional threads are generated
-internally to handle the asynchronous offload tasks. :l
-
-If running short benchmark runs with dynamic load balancing, adding a
-short warm-up run (10-20 steps) will allow the load-balancer to find a
-near-optimal setting that will carry over to additional runs. :l
-
-If pair computations are being offloaded to an Intel(R) Xeon Phi(TM)
-coprocessor, a diagnostic line is printed to the screen (not to the
-log file), during the setup phase of a run, indicating that offload
-mode is being used and indicating the number of coprocessor threads
-per MPI task.  Additionally, an offload timing summary is printed at
-the end of each run.  When offloading, the frequency for "atom
-sorting"_atom_modify.html is changed to 1 so that the per-atom data is
-effectively sorted at every rebuild of the neighbor lists. :l
-
-For simulations with long-range electrostatics or bond, angle,
-dihedral, improper calculations, computation and data transfer to the
-coprocessor will run concurrently with computations and MPI
-communications for these calculations on the host CPU.  The USER-INTEL
-package has two modes for deciding which atoms will be handled by the
-coprocessor.  This choice is controlled with the {ghost} keyword of
-the "package intel"_package.html command.  When set to 0, ghost atoms
-(atoms at the borders between MPI tasks) are not offloaded to the
-card.  This allows for overlap of MPI communication of forces with
-computation on the coprocessor when the "newton"_newton.html setting
-is "on".  The default is dependent on the style being used, however,
-better performance may be achieved by setting this option
-explictly. :l,ule
-
-[Restrictions:]
-
-When offloading to a coprocessor, "hybrid"_pair_hybrid.html styles
-that require skip lists for neighbor builds cannot be offloaded.
-Using "hybrid/overlay"_pair_hybrid.html is allowed.  Only one intel
-accelerated style may be used with hybrid styles.
-"Special_bonds"_special_bonds.html exclusion lists are not currently
-supported with offload, however, the same effect can often be
-accomplished by setting cutoffs for excluded atom types to 0.  None of
-the pair styles in the USER-INTEL package currently support the
-"inner", "middle", "outer" options for rRESPA integration via the
-"run_style respa"_run_style.html command; only the "pair" option is
-supported.

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-  <p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
-<div class="section" id="kokkos-package">
-<h1>5.KOKKOS package<a class="headerlink" href="#kokkos-package" title="Permalink to this headline">¶</a></h1>
-<p>The KOKKOS package was developed primarily by Christian Trott (Sandia)
-with contributions of various styles by others, including Sikandar
-Mashayak (UIUC), Stan Moore (Sandia), and Ray Shan (Sandia).  The
-underlying Kokkos library was written primarily by Carter Edwards,
-Christian Trott, and Dan Sunderland (all Sandia).</p>
-<p>The KOKKOS package contains versions of pair, fix, and atom styles
-that use data structures and macros provided by the Kokkos library,
-which is included with LAMMPS in lib/kokkos.</p>
-<p>The Kokkos library is part of
-<a class="reference external" href="http://trilinos.sandia.gov/packages/kokkos">Trilinos</a> and can also be
-downloaded from <a class="reference external" href="https://github.com/kokkos/kokkos">Github</a>. Kokkos is a
-templated C++ library that provides two key abstractions for an
-application like LAMMPS.  First, it allows a single implementation of
-an application kernel (e.g. a pair style) to run efficiently on
-different kinds of hardware, such as a GPU, Intel Phi, or many-core
-CPU.</p>
-<p>The Kokkos library also provides data abstractions to adjust (at
-compile time) the memory layout of basic data structures like 2d and
-3d arrays and allow the transparent utilization of special hardware
-load and store operations.  Such data structures are used in LAMMPS to
-store atom coordinates or forces or neighbor lists.  The layout is
-chosen to optimize performance on different platforms.  Again this
-functionality is hidden from the developer, and does not affect how
-the kernel is coded.</p>
-<p>These abstractions are set at build time, when LAMMPS is compiled with
-the KOKKOS package installed.  All Kokkos operations occur within the
-context of an individual MPI task running on a single node of the
-machine.  The total number of MPI tasks used by LAMMPS (one or
-multiple per compute node) is set in the usual manner via the mpirun
-or mpiexec commands, and is independent of Kokkos.</p>
-<p>Kokkos currently provides support for 3 modes of execution (per MPI
-task).  These are OpenMP (for many-core CPUs), Cuda (for NVIDIA GPUs),
-and OpenMP (for Intel Phi).  Note that the KOKKOS package supports
-running on the Phi in native mode, not offload mode like the
-USER-INTEL package supports.  You choose the mode at build time to
-produce an executable compatible with specific hardware.</p>
-<p>Here is a quick overview of how to use the KOKKOS package
-for CPU acceleration, assuming one or more 16-core nodes.
-More details follow.</p>
-<p>use a C++11 compatible compiler
-make yes-kokkos
-make mpi KOKKOS_DEVICES=OpenMP                 # build with the KOKKOS package
-make kokkos_omp                                # or Makefile.kokkos_omp already has variable set
-Make.py -v -p kokkos -kokkos omp -o mpi -a file mpi   # or one-line build via Make.py</p>
-<div class="highlight-python"><div class="highlight"><pre>mpirun -np 16 lmp_mpi -k on -sf kk -in in.lj              # 1 node, 16 MPI tasks/node, no threads
-mpirun -np 2 -ppn 1 lmp_mpi -k on t 16 -sf kk -in in.lj   # 2 nodes, 1 MPI task/node, 16 threads/task
-mpirun -np 2 lmp_mpi -k on t 8 -sf kk -in in.lj           # 1 node, 2 MPI tasks/node, 8 threads/task
-mpirun -np 32 -ppn 4 lmp_mpi -k on t 4 -sf kk -in in.lj   # 8 nodes, 4 MPI tasks/node, 4 threads/task
-</pre></div>
-</div>
-<ul class="simple">
-<li>specify variables and settings in your Makefile.machine that enable OpenMP, GPU, or Phi support</li>
-<li>include the KOKKOS package and build LAMMPS</li>
-<li>enable the KOKKOS package and its hardware options via the &#8220;-k on&#8221; command-line switch use KOKKOS styles in your input script</li>
-</ul>
-<p>Here is a quick overview of how to use the KOKKOS package for GPUs,
-assuming one or more nodes, each with 16 cores and a GPU.  More
-details follow.</p>
-<p>discuss use of NVCC, which Makefiles to examine</p>
-<p>use a C++11 compatible compiler
-KOKKOS_DEVICES = Cuda, OpenMP
-KOKKOS_ARCH = Kepler35
-make yes-kokkos
-make machine
-Make.py -p kokkos -kokkos cuda arch=31 -o kokkos_cuda -a file kokkos_cuda</p>
-<div class="highlight-python"><div class="highlight"><pre>mpirun -np 1 lmp_cuda -k on t 6 -sf kk -in in.lj          # one MPI task, 6 threads on CPU
-mpirun -np 4 -ppn 1 lmp_cuda -k on t 6 -sf kk -in in.lj   # ditto on 4 nodes
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre>mpirun -np 2 lmp_cuda -k on t 8 g 2 -sf kk -in in.lj           # two MPI tasks, 8 threads per CPU
-mpirun -np 32 -ppn 2 lmp_cuda -k on t 8 g 2 -sf kk -in in.lj   # ditto on 16 nodes
-</pre></div>
-</div>
-<p>Here is a quick overview of how to use the KOKKOS package
-for the Intel Phi:</p>
-<div class="highlight-python"><div class="highlight"><pre>use a C++11 compatible compiler
-KOKKOS_DEVICES = OpenMP
-KOKKOS_ARCH = KNC
-make yes-kokkos
-make machine
-Make.py -p kokkos -kokkos phi -o kokkos_phi -a file mpi
-</pre></div>
-</div>
-<p>host=MIC, Intel Phi with 61 cores (240 threads/phi via 4x hardware threading):
-mpirun -np 1 lmp_g++ -k on t 240 -sf kk -in in.lj           # 1 MPI task on 1 Phi, 1*240 = 240
-mpirun -np 30 lmp_g++ -k on t 8 -sf kk -in in.lj            # 30 MPI tasks on 1 Phi, 30*8 = 240
-mpirun -np 12 lmp_g++ -k on t 20 -sf kk -in in.lj           # 12 MPI tasks on 1 Phi, 12*20 = 240
-mpirun -np 96 -ppn 12 lmp_g++ -k on t 20 -sf kk -in in.lj   # ditto on 8 Phis</p>
-<p><strong>Required hardware/software:</strong></p>
-<p>Kokkos support within LAMMPS must be built with a C++11 compatible
-compiler.  If using gcc, version 4.8.1 or later is required.</p>
-<p>To build with Kokkos support for CPUs, your compiler must support the
-OpenMP interface.  You should have one or more multi-core CPUs so that
-multiple threads can be launched by each MPI task running on a CPU.</p>
-<p>To build with Kokkos support for NVIDIA GPUs, NVIDIA Cuda software
-version 6.5 or later must be installed on your system.  See the
-discussion for the <a class="reference internal" href="accelerate_cuda.html"><em>USER-CUDA</em></a> and
-<a class="reference internal" href="accelerate_gpu.html"><em>GPU</em></a> packages for details of how to check and do
-this.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">For good performance of the KOKKOS package on GPUs,
-you must have Kepler generation GPUs (or later).  The Kokkos library
-exploits texture cache options not supported by Telsa generation GPUs
-(or older).</p>
-</div>
-<p>To build with Kokkos support for Intel Xeon Phi coprocessors, your
-sysmte must be configured to use them in &#8220;native&#8221; mode, not &#8220;offload&#8221;
-mode like the USER-INTEL package supports.</p>
-<p><strong>Building LAMMPS with the KOKKOS package:</strong></p>
-<p>You must choose at build time whether to build for CPUs (OpenMP),
-GPUs, or Phi.</p>
-<p>You can do any of these in one line, using the src/Make.py script,
-described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.
-Type &#8220;Make.py -h&#8221; for help.  If run from the src directory, these
-commands will create src/lmp_kokkos_omp, lmp_kokkos_cuda, and
-lmp_kokkos_phi.  Note that the OMP and PHI options use
-src/MAKE/Makefile.mpi as the starting Makefile.machine.  The CUDA
-option uses src/MAKE/OPTIONS/Makefile.kokkos_cuda.</p>
-<p>The latter two steps can be done using the &#8220;-k on&#8221;, &#8220;-pk kokkos&#8221; and
-&#8220;-sf kk&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switches</span></a>
-respectively.  Or the effect of the &#8220;-pk&#8221; or &#8220;-sf&#8221; switches can be
-duplicated by adding the <a class="reference internal" href="package.html"><em>package kokkos</em></a> or <a class="reference internal" href="suffix.html"><em>suffix kk</em></a> commands respectively to your input script.</p>
-<p>Or you can follow these steps:</p>
-<p>CPU-only (run all-MPI or with OpenMP threading):</p>
-<div class="highlight-python"><div class="highlight"><pre>cd lammps/src
-make yes-kokkos
-make g++ KOKKOS_DEVICES=OpenMP
-</pre></div>
-</div>
-<p>Intel Xeon Phi:</p>
-<div class="highlight-python"><div class="highlight"><pre>cd lammps/src
-make yes-kokkos
-make g++ KOKKOS_DEVICES=OpenMP KOKKOS_ARCH=KNC
-</pre></div>
-</div>
-<p>CPUs and GPUs:</p>
-<div class="highlight-python"><div class="highlight"><pre>cd lammps/src
-make yes-kokkos
-make cuda KOKKOS_DEVICES=Cuda
-</pre></div>
-</div>
-<p>These examples set the KOKKOS-specific OMP, MIC, CUDA variables on the
-make command line which requires a GNU-compatible make command.  Try
-&#8220;gmake&#8221; if your system&#8217;s standard make complains.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">If you build using make line variables and re-build
-LAMMPS twice with different KOKKOS options and the <em>same</em> target,
-e.g. g++ in the first two examples above, then you <em>must</em> perform a
-&#8220;make clean-all&#8221; or &#8220;make clean-machine&#8221; before each build.  This is
-to force all the KOKKOS-dependent files to be re-compiled with the new
-options.</p>
-</div>
-<p>You can also hardwire these make variables in the specified machine
-makefile, e.g. src/MAKE/Makefile.g++ in the first two examples above,
-with a line like:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="n">KOKKOS_ARCH</span> <span class="o">=</span> <span class="n">KNC</span>
-</pre></div>
-</div>
-<p>Note that if you build LAMMPS multiple times in this manner, using
-different KOKKOS options (defined in different machine makefiles), you
-do not have to worry about doing a &#8220;clean&#8221; in between.  This is
-because the targets will be different.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">The 3rd example above for a GPU, uses a different
-machine makefile, in this case src/MAKE/Makefile.cuda, which is
-included in the LAMMPS distribution.  To build the KOKKOS package for
-a GPU, this makefile must use the NVIDA &#8220;nvcc&#8221; compiler.  And it must
-have a KOKKOS_ARCH setting that is appropriate for your NVIDIA
-hardware and installed software.  Typical values for KOKKOS_ARCH are given
-below, as well
-as other settings that must be included in the machine makefile, if
-you create your own.</p>
-</div>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">Currently, there are no precision options with the
-KOKKOS package.  All compilation and computation is performed in
-double precision.</p>
-</div>
-<p>There are other allowed options when building with the KOKKOS package.
-As above, they can be set either as variables on the make command line
-or in Makefile.machine.  This is the full list of options, including
-those discussed above, Each takes a value shown below.  The
-default value is listed, which is set in the
-lib/kokkos/Makefile.kokkos file.</p>
-<p>#Default settings specific options
-#Options: force_uvm,use_ldg,rdc</p>
-<ul class="simple">
-<li>KOKKOS_DEVICES, values = <em>OpenMP</em>, <em>Serial</em>, <em>Pthreads</em>, <em>Cuda</em>, default = <em>OpenMP</em></li>
-<li>KOKKOS_ARCH, values = <em>KNC</em>, <em>SNB</em>, <em>HSW</em>, <em>Kepler</em>, <em>Kepler30</em>, <em>Kepler32</em>, <em>Kepler35</em>, <em>Kepler37</em>, <em>Maxwell</em>, <em>Maxwell50</em>, <em>Maxwell52</em>, <em>Maxwell53</em>, <em>ARMv8</em>, <em>BGQ</em>, <em>Power7</em>, <em>Power8</em>, default = <em>none</em></li>
-<li>KOKKOS_DEBUG, values = <em>yes</em>, <em>no</em>, default = <em>no</em></li>
-<li>KOKKOS_USE_TPLS, values = <em>hwloc</em>, <em>librt</em>, default = <em>none</em></li>
-<li>KOKKOS_CUDA_OPTIONS, values = <em>force_uvm</em>, <em>use_ldg</em>, <em>rdc</em></li>
-</ul>
-<p>KOKKOS_DEVICE sets the parallelization method used for Kokkos code
-(within LAMMPS).  KOKKOS_DEVICES=OpenMP means that OpenMP will be
-used.  KOKKOS_DEVICES=Pthreads means that pthreads will be used.
-KOKKOS_DEVICES=Cuda means an NVIDIA GPU running CUDA will be used.</p>
-<p>If KOKKOS_DEVICES=Cuda, then the lo-level Makefile in the src/MAKE
-directory must use &#8220;nvcc&#8221; as its compiler, via its CC setting.  For
-best performance its CCFLAGS setting should use -O3 and have a
-KOKKOS_ARCH setting that matches the compute capability of your NVIDIA
-hardware and software installation, e.g. KOKKOS_ARCH=Kepler30.  Note
-the minimal required compute capability is 2.0, but this will give
-signicantly reduced performance compared to Kepler generation GPUs
-with compute capability 3.x.  For the LINK setting, &#8220;nvcc&#8221; should not
-be used; instead use g++ or another compiler suitable for linking C++
-applications.  Often you will want to use your MPI compiler wrapper
-for this setting (i.e. mpicxx).  Finally, the lo-level Makefile must
-also have a &#8220;Compilation rule&#8221; for creating <a href="#id1"><span class="problematic" id="id2">*</span></a>.o files from <a href="#id3"><span class="problematic" id="id4">*</span></a>.cu files.
-See src/Makefile.cuda for an example of a lo-level Makefile with all
-of these settings.</p>
-<p>KOKKOS_USE_TPLS=hwloc binds threads to hardware cores, so they do not
-migrate during a simulation.  KOKKOS_USE_TPLS=hwloc should always be
-used if running with KOKKOS_DEVICES=Pthreads for pthreads.  It is not
-necessary for KOKKOS_DEVICES=OpenMP for OpenMP, because OpenMP
-provides alternative methods via environment variables for binding
-threads to hardware cores.  More info on binding threads to cores is
-given in <span class="xref std std-ref">this section</span>.</p>
-<p>KOKKOS_ARCH=KNC enables compiler switches needed when compling for an
-Intel Phi processor.</p>
-<p>KOKKOS_USE_TPLS=librt enables use of a more accurate timer mechanism
-on most Unix platforms.  This library is not available on all
-platforms.</p>
-<p>KOKKOS_DEBUG is only useful when developing a Kokkos-enabled style
-within LAMMPS.  KOKKOS_DEBUG=yes enables printing of run-time
-debugging information that can be useful.  It also enables runtime
-bounds checking on Kokkos data structures.</p>
-<p>KOKKOS_CUDA_OPTIONS are additional options for CUDA.</p>
-<p>For more information on Kokkos see the Kokkos programmers&#8217; guide here:
-/lib/kokkos/doc/Kokkos_PG.pdf.</p>
-<p><strong>Run with the KOKKOS package from the command line:</strong></p>
-<p>The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.</p>
-<p>When using KOKKOS built with host=OMP, you need to choose how many
-OpenMP threads per MPI task will be used (via the &#8220;-k&#8221; command-line
-switch discussed below).  Note that the product of MPI tasks * OpenMP
-threads/task should not exceed the physical number of cores (on a
-node), otherwise performance will suffer.</p>
-<p>When using the KOKKOS package built with device=CUDA, you must use
-exactly one MPI task per physical GPU.</p>
-<p>When using the KOKKOS package built with host=MIC for Intel Xeon Phi
-coprocessor support you need to insure there are one or more MPI tasks
-per coprocessor, and choose the number of coprocessor threads to use
-per MPI task (via the &#8220;-k&#8221; command-line switch discussed below).  The
-product of MPI tasks * coprocessor threads/task should not exceed the
-maximum number of threads the coproprocessor is designed to run,
-otherwise performance will suffer.  This value is 240 for current
-generation Xeon Phi(TM) chips, which is 60 physical cores * 4
-threads/core.  Note that with the KOKKOS package you do not need to
-specify how many Phi coprocessors there are per node; each
-coprocessors is simply treated as running some number of MPI tasks.</p>
-<p>You must use the &#8220;-k on&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to enable the KOKKOS package.  It
-takes additional arguments for hardware settings appropriate to your
-system.  Those arguments are <a class="reference internal" href="Section_start.html#start-7"><span>documented here</span></a>.  The two most commonly used
-options are:</p>
-<div class="highlight-python"><div class="highlight"><pre>-k on t Nt g Ng
-</pre></div>
-</div>
-<p>The &#8220;t Nt&#8221; option applies to host=OMP (even if device=CUDA) and
-host=MIC.  For host=OMP, it specifies how many OpenMP threads per MPI
-task to use with a node.  For host=MIC, it specifies how many Xeon Phi
-threads per MPI task to use within a node.  The default is Nt = 1.
-Note that for host=OMP this is effectively MPI-only mode which may be
-fine.  But for host=MIC you will typically end up using far less than
-all the 240 available threads, which could give very poor performance.</p>
-<p>The &#8220;g Ng&#8221; option applies to device=CUDA.  It specifies how many GPUs
-per compute node to use.  The default is 1, so this only needs to be
-specified is you have 2 or more GPUs per compute node.</p>
-<p>The &#8220;-k on&#8221; switch also issues a &#8220;package kokkos&#8221; command (with no
-additional arguments) which sets various KOKKOS options to default
-values, as discussed on the <a class="reference internal" href="package.html"><em>package</em></a> command doc page.</p>
-<p>Use the &#8220;-sf kk&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>,
-which will automatically append &#8220;kk&#8221; to styles that support it.  Use
-the &#8220;-pk kokkos&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> if
-you wish to change any of the default <a class="reference internal" href="package.html"><em>package kokkos</em></a>
-optionns set by the &#8220;-k on&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>.</p>
-<p>Note that the default for the <a class="reference internal" href="package.html"><em>package kokkos</em></a> command is
-to use &#8220;full&#8221; neighbor lists and set the Newton flag to &#8220;off&#8221; for both
-pairwise and bonded interactions.  This typically gives fastest
-performance.  If the <a class="reference internal" href="newton.html"><em>newton</em></a> command is used in the input
-script, it can override the Newton flag defaults.</p>
-<p>However, when running in MPI-only mode with 1 thread per MPI task, it
-will typically be faster to use &#8220;half&#8221; neighbor lists and set the
-Newton flag to &#8220;on&#8221;, just as is the case for non-accelerated pair
-styles.  You can do this with the &#8220;-pk&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>.</p>
-<p><strong>Or run with the KOKKOS package by editing an input script:</strong></p>
-<p>The discussion above for the mpirun/mpiexec command and setting
-appropriate thread and GPU values for host=OMP or host=MIC or
-device=CUDA are the same.</p>
-<p>You must still use the &#8220;-k on&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to enable the KOKKOS package, and
-specify its additional arguments for hardware options appopriate to
-your system, as documented above.</p>
-<p>Use the <a class="reference internal" href="suffix.html"><em>suffix kk</em></a> command, or you can explicitly add a
-&#8220;kk&#8221; suffix to individual styles in your input script, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/kk 2.5
-</pre></div>
-</div>
-<p>You only need to use the <a class="reference internal" href="package.html"><em>package kokkos</em></a> command if you
-wish to change any of its option defaults, as set by the &#8220;-k on&#8221;
-<a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>.</p>
-<p><strong>Speed-ups to expect:</strong></p>
-<p>The performance of KOKKOS running in different modes is a function of
-your hardware, which KOKKOS-enable styles are used, and the problem
-size.</p>
-<p>Generally speaking, the following rules of thumb apply:</p>
-<ul class="simple">
-<li>When running on CPUs only, with a single thread per MPI task,
-performance of a KOKKOS style is somewhere between the standard
-(un-accelerated) styles (MPI-only mode), and those provided by the
-USER-OMP package.  However the difference between all 3 is small (less
-than 20%).</li>
-<li>When running on CPUs only, with multiple threads per MPI task,
-performance of a KOKKOS style is a bit slower than the USER-OMP
-package.</li>
-<li>When running on GPUs, KOKKOS is typically faster than the USER-CUDA
-and GPU packages.</li>
-<li>When running on Intel Xeon Phi, KOKKOS is not as fast as
-the USER-INTEL package, which is optimized for that hardware.</li>
-</ul>
-<p>See the <a class="reference external" href="http://lammps.sandia.gov/bench.html">Benchmark page</a> of the
-LAMMPS web site for performance of the KOKKOS package on different
-hardware.</p>
-<p><strong>Guidelines for best performance:</strong></p>
-<p>Here are guidline for using the KOKKOS package on the different
-hardware configurations listed above.</p>
-<p>Many of the guidelines use the <a class="reference internal" href="package.html"><em>package kokkos</em></a> command
-See its doc page for details and default settings.  Experimenting with
-its options can provide a speed-up for specific calculations.</p>
-<p><strong>Running on a multi-core CPU:</strong></p>
-<p>If N is the number of physical cores/node, then the number of MPI
-tasks/node * number of threads/task should not exceed N, and should
-typically equal N.  Note that the default threads/task is 1, as set by
-the &#8220;t&#8221; keyword of the &#8220;-k&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>.  If you do not change this, no
-additional parallelism (beyond MPI) will be invoked on the host
-CPU(s).</p>
-<p>You can compare the performance running in different modes:</p>
-<ul class="simple">
-<li>run with 1 MPI task/node and N threads/task</li>
-<li>run with N MPI tasks/node and 1 thread/task</li>
-<li>run with settings in between these extremes</li>
-</ul>
-<p>Examples of mpirun commands in these modes are shown above.</p>
-<p>When using KOKKOS to perform multi-threading, it is important for
-performance to bind both MPI tasks to physical cores, and threads to
-physical cores, so they do not migrate during a simulation.</p>
-<p>If you are not certain MPI tasks are being bound (check the defaults
-for your MPI installation), binding can be forced with these flags:</p>
-<div class="highlight-python"><div class="highlight"><pre>OpenMPI 1.8: mpirun -np 2 -bind-to socket -map-by socket ./lmp_openmpi ...
-Mvapich2 2.0: mpiexec -np 2 -bind-to socket -map-by socket ./lmp_mvapich ...
-</pre></div>
-</div>
-<p>For binding threads with the KOKKOS OMP option, use thread affinity
-environment variables to force binding.  With OpenMP 3.1 (gcc 4.7 or
-later, intel 12 or later) setting the environment variable
-OMP_PROC_BIND=true should be sufficient.  For binding threads with the
-KOKKOS pthreads option, compile LAMMPS the KOKKOS HWLOC=yes option, as
-discussed in <a class="reference internal" href="Section_start.html#start-3-4"><span>Section 2.3.4</span></a> of the
-manual.</p>
-<p><strong>Running on GPUs:</strong></p>
-<p>Insure the -arch setting in the machine makefile you are using,
-e.g. src/MAKE/Makefile.cuda, is correct for your GPU hardware/software
-(see <a class="reference internal" href="Section_start.html#start-3-4"><span>this section</span></a> of the manual for
-details).</p>
-<p>The -np setting of the mpirun command should set the number of MPI
-tasks/node to be equal to the # of physical GPUs on the node.</p>
-<p>Use the &#8220;-k&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a> to
-specify the number of GPUs per node, and the number of threads per MPI
-task.  As above for multi-core CPUs (and no GPU), if N is the number
-of physical cores/node, then the number of MPI tasks/node * number of
-threads/task should not exceed N.  With one GPU (and one MPI task) it
-may be faster to use less than all the available cores, by setting
-threads/task to a smaller value.  This is because using all the cores
-on a dual-socket node will incur extra cost to copy memory from the
-2nd socket to the GPU.</p>
-<p>Examples of mpirun commands that follow these rules are shown above.</p>
-<div class="admonition warning">
-<p class="first admonition-title">Warning</p>
-<p class="last">When using a GPU, you will achieve the best
-performance if your input script does not use any fix or compute
-styles which are not yet Kokkos-enabled.  This allows data to stay on
-the GPU for multiple timesteps, without being copied back to the host
-CPU.  Invoking a non-Kokkos fix or compute, or performing I/O for
-<a class="reference internal" href="thermo_style.html"><em>thermo</em></a> or <a class="reference internal" href="dump.html"><em>dump</em></a> output will cause data
-to be copied back to the CPU.</p>
-</div>
-<p>You cannot yet assign multiple MPI tasks to the same GPU with the
-KOKKOS package.  We plan to support this in the future, similar to the
-GPU package in LAMMPS.</p>
-<p>You cannot yet use both the host (multi-threaded) and device (GPU)
-together to compute pairwise interactions with the KOKKOS package.  We
-hope to support this in the future, similar to the GPU package in
-LAMMPS.</p>
-<p><strong>Running on an Intel Phi:</strong></p>
-<p>Kokkos only uses Intel Phi processors in their &#8220;native&#8221; mode, i.e.
-not hosted by a CPU.</p>
-<p>As illustrated above, build LAMMPS with OMP=yes (the default) and
-MIC=yes.  The latter insures code is correctly compiled for the Intel
-Phi.  The OMP setting means OpenMP will be used for parallelization on
-the Phi, which is currently the best option within Kokkos.  In the
-future, other options may be added.</p>
-<p>Current-generation Intel Phi chips have either 61 or 57 cores.  One
-core should be excluded for running the OS, leaving 60 or 56 cores.
-Each core is hyperthreaded, so there are effectively N = 240 (4*60) or
-N = 224 (4*56) cores to run on.</p>
-<p>The -np setting of the mpirun command sets the number of MPI
-tasks/node.  The &#8220;-k on t Nt&#8221; command-line switch sets the number of
-threads/task as Nt.  The product of these 2 values should be N, i.e.
-240 or 224.  Also, the number of threads/task should be a multiple of
-4 so that logical threads from more than one MPI task do not run on
-the same physical core.</p>
-<p>Examples of mpirun commands that follow these rules are shown above.</p>
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>As noted above, if using GPUs, the number of MPI tasks per compute
-node should equal to the number of GPUs per compute node.  In the
-future Kokkos will support assigning multiple MPI tasks to a single
-GPU.</p>
-<p>Currently Kokkos does not support AMD GPUs due to limits in the
-available backend programming models.  Specifically, Kokkos requires
-extensive C++ support from the Kernel language.  This is expected to
-change in the future.</p>
-</div>
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-            
-  <p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
-<div class="section" id="user-omp-package">
-<h1>5.USER-OMP package<a class="headerlink" href="#user-omp-package" title="Permalink to this headline">¶</a></h1>
-<p>The USER-OMP package was developed by Axel Kohlmeyer at Temple
-University.  It provides multi-threaded versions of most pair styles,
-nearly all bonded styles (bond, angle, dihedral, improper), several
-Kspace styles, and a few fix styles.  The package currently uses the
-OpenMP interface for multi-threading.</p>
-<p>Here is a quick overview of how to use the USER-OMP package, assuming
-one or more 16-core nodes.  More details follow.</p>
-<div class="highlight-python"><div class="highlight"><pre>use -fopenmp with CCFLAGS and LINKFLAGS in Makefile.machine
-make yes-user-omp
-make mpi                                   # build with USER-OMP package, if settings added to Makefile.mpi
-make omp                                   # or Makefile.omp already has settings
-Make.py -v -p omp -o mpi -a file mpi       # or one-line build via Make.py
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre>lmp_mpi -sf omp -pk omp 16 &lt; in.script                         # 1 MPI task, 16 threads
-mpirun -np 4 lmp_mpi -sf omp -pk omp 4 -in in.script           # 4 MPI tasks, 4 threads/task
-mpirun -np 32 -ppn 4 lmp_mpi -sf omp -pk omp 4 -in in.script   # 8 nodes, 4 MPI tasks/node, 4 threads/task
-</pre></div>
-</div>
-<p><strong>Required hardware/software:</strong></p>
-<p>Your compiler must support the OpenMP interface.  You should have one
-or more multi-core CPUs so that multiple threads can be launched by
-each MPI task running on a CPU.</p>
-<p><strong>Building LAMMPS with the USER-OMP package:</strong></p>
-<p>The lines above illustrate how to include/build with the USER-OMP
-package in two steps, using the &#8220;make&#8221; command.  Or how to do it with
-one command via the src/Make.py script, described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.  Type &#8220;Make.py -h&#8221; for
-help.</p>
-<p>Note that the CCFLAGS and LINKFLAGS settings in Makefile.machine must
-include &#8220;-fopenmp&#8221;.  Likewise, if you use an Intel compiler, the
-CCFLAGS setting must include &#8220;-restrict&#8221;.  The Make.py command will
-add these automatically.</p>
-<p><strong>Run with the USER-OMP package from the command line:</strong></p>
-<p>The mpirun or mpiexec command sets the total number of MPI tasks used
-by LAMMPS (one or multiple per compute node) and the number of MPI
-tasks used per node.  E.g. the mpirun command in MPICH does this via
-its -np and -ppn switches.  Ditto for OpenMPI via -np and -npernode.</p>
-<p>You need to choose how many OpenMP threads per MPI task will be used
-by the USER-OMP package.  Note that the product of MPI tasks *
-threads/task should not exceed the physical number of cores (on a
-node), otherwise performance will suffer.</p>
-<p>As in the lines above, use the &#8220;-sf omp&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>, which will automatically append
-&#8220;omp&#8221; to styles that support it.  The &#8220;-sf omp&#8221; switch also issues a
-default <a class="reference internal" href="package.html"><em>package omp 0</em></a> command, which will set the
-number of threads per MPI task via the OMP_NUM_THREADS environment
-variable.</p>
-<p>You can also use the &#8220;-pk omp Nt&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>, to explicitly set Nt = # of OpenMP
-threads per MPI task to use, as well as additional options.  Its
-syntax is the same as the <a class="reference internal" href="package.html"><em>package omp</em></a> command whose doc
-page gives details, including the default values used if it is not
-specified.  It also gives more details on how to set the number of
-threads via the OMP_NUM_THREADS environment variable.</p>
-<p><strong>Or run with the USER-OMP package by editing an input script:</strong></p>
-<p>The discussion above for the mpirun/mpiexec command, MPI tasks/node,
-and threads/MPI task is the same.</p>
-<p>Use the <a class="reference internal" href="suffix.html"><em>suffix omp</em></a> command, or you can explicitly add an
-&#8220;omp&#8221; suffix to individual styles in your input script, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/omp 2.5
-</pre></div>
-</div>
-<p>You must also use the <a class="reference internal" href="package.html"><em>package omp</em></a> command to enable the
-USER-OMP package.  When you do this you also specify how many threads
-per MPI task to use.  The command doc page explains other options and
-how to set the number of threads via the OMP_NUM_THREADS environment
-variable.</p>
-<p><strong>Speed-ups to expect:</strong></p>
-<p>Depending on which styles are accelerated, you should look for a
-reduction in the &#8220;Pair time&#8221;, &#8220;Bond time&#8221;, &#8220;KSpace time&#8221;, and &#8220;Loop
-time&#8221; values printed at the end of a run.</p>
-<p>You may see a small performance advantage (5 to 20%) when running a
-USER-OMP style (in serial or parallel) with a single thread per MPI
-task, versus running standard LAMMPS with its standard un-accelerated
-styles (in serial or all-MPI parallelization with 1 task/core).  This
-is because many of the USER-OMP styles contain similar optimizations
-to those used in the OPT package, described in <a class="reference internal" href="accelerate_opt.html"><em>Section accelerate 5.3.6</em></a>.</p>
-<p>With multiple threads/task, the optimal choice of number of MPI
-tasks/node and OpenMP threads/task can vary a lot and should always be
-tested via benchmark runs for a specific simulation running on a
-specific machine, paying attention to guidelines discussed in the next
-sub-section.</p>
-<p>A description of the multi-threading strategy used in the USER-OMP
-package and some performance examples are <a class="reference external" href="http://sites.google.com/site/akohlmey/software/lammps-icms/lammps-icms-tms2011-talk.pdf?attredirects=0&amp;d=1">presented here</a></p>
-<p><strong>Guidelines for best performance:</strong></p>
-<p>For many problems on current generation CPUs, running the USER-OMP
-package with a single thread/task is faster than running with multiple
-threads/task.  This is because the MPI parallelization in LAMMPS is
-often more efficient than multi-threading as implemented in the
-USER-OMP package.  The parallel efficiency (in a threaded sense) also
-varies for different USER-OMP styles.</p>
-<p>Using multiple threads/task can be more effective under the following
-circumstances:</p>
-<ul class="simple">
-<li>Individual compute nodes have a significant number of CPU cores but
-the CPU itself has limited memory bandwidth, e.g. for Intel Xeon 53xx
-(Clovertown) and 54xx (Harpertown) quad-core processors.  Running one
-MPI task per CPU core will result in significant performance
-degradation, so that running with 4 or even only 2 MPI tasks per node
-is faster.  Running in hybrid MPI+OpenMP mode will reduce the
-inter-node communication bandwidth contention in the same way, but
-offers an additional speedup by utilizing the otherwise idle CPU
-cores.</li>
-<li>The interconnect used for MPI communication does not provide
-sufficient bandwidth for a large number of MPI tasks per node.  For
-example, this applies to running over gigabit ethernet or on Cray XT4
-or XT5 series supercomputers.  As in the aforementioned case, this
-effect worsens when using an increasing number of nodes.</li>
-<li>The system has a spatially inhomogeneous particle density which does
-not map well to the <a class="reference internal" href="processors.html"><em>domain decomposition scheme</em></a> or
-<a class="reference internal" href="balance.html"><em>load-balancing</em></a> options that LAMMPS provides.  This is
-because multi-threading achives parallelism over the number of
-particles, not via their distribution in space.</li>
-<li>A machine is being used in &#8220;capability mode&#8221;, i.e. near the point
-where MPI parallelism is maxed out.  For example, this can happen when
-using the <a class="reference internal" href="kspace_style.html"><em>PPPM solver</em></a> for long-range
-electrostatics on large numbers of nodes.  The scaling of the KSpace
-calculation (see the <a class="reference internal" href="kspace_style.html"><em>kspace_style</em></a> command) becomes
-the performance-limiting factor.  Using multi-threading allows less
-MPI tasks to be invoked and can speed-up the long-range solver, while
-increasing overall performance by parallelizing the pairwise and
-bonded calculations via OpenMP.  Likewise additional speedup can be
-sometimes be achived by increasing the length of the Coulombic cutoff
-and thus reducing the work done by the long-range solver.  Using the
-<a class="reference internal" href="run_style.html"><em>run_style verlet/split</em></a> command, which is compatible
-with the USER-OMP package, is an alternative way to reduce the number
-of MPI tasks assigned to the KSpace calculation.</li>
-</ul>
-<p>Additional performance tips are as follows:</p>
-<ul class="simple">
-<li>The best parallel efficiency from <em>omp</em> styles is typically achieved
-when there is at least one MPI task per physical CPU chip, i.e. socket
-or die.</li>
-<li>It is usually most efficient to restrict threading to a single
-socket, i.e. use one or more MPI task per socket.</li>
-<li>IMPORTANT NOTE: By default, several current MPI implementations use a
-processor affinity setting that restricts each MPI task to a single
-CPU core.  Using multi-threading in this mode will force all threads
-to share the one core and thus is likely to be counterproductive.
-Instead, binding MPI tasks to a (multi-core) socket, should solve this
-issue.</li>
-</ul>
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>None.</p>
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-            
-  <p><a class="reference internal" href="Section_accelerate.html"><em>Return to Section accelerate overview</em></a></p>
-<div class="section" id="opt-package">
-<h1>5.OPT package<a class="headerlink" href="#opt-package" title="Permalink to this headline">¶</a></h1>
-<p>The OPT package was developed by James Fischer (High Performance
-Technologies), David Richie, and Vincent Natoli (Stone Ridge
-Technologies).  It contains a handful of pair styles whose compute()
-methods were rewritten in C++ templated form to reduce the overhead
-due to if tests and other conditional code.</p>
-<p>Here is a quick overview of how to use the OPT package.  More details
-follow.</p>
-<div class="highlight-python"><div class="highlight"><pre>make yes-opt
-make mpi                               # build with the OPT pacakge
-Make.py -v -p opt -o mpi -a file mpi   # or one-line build via Make.py
-</pre></div>
-</div>
-<div class="highlight-python"><div class="highlight"><pre>lmp_mpi -sf opt -in in.script                # run in serial
-mpirun -np 4 lmp_mpi -sf opt -in in.script   # run in parallel
-</pre></div>
-</div>
-<p><strong>Required hardware/software:</strong></p>
-<p>None.</p>
-<p><strong>Building LAMMPS with the OPT package:</strong></p>
-<p>The lines above illustrate how to build LAMMPS with the OPT package in
-two steps, using the &#8220;make&#8221; command.  Or how to do it with one command
-via the src/Make.py script, described in <a class="reference internal" href="Section_start.html#start-4"><span>Section 2.4</span></a> of the manual.  Type &#8220;Make.py -h&#8221; for
-help.</p>
-<p>Note that if you use an Intel compiler to build with the OPT package,
-the CCFLAGS setting in your Makefile.machine must include &#8220;-restrict&#8221;.
-The Make.py command will add this automatically.</p>
-<p><strong>Run with the OPT package from the command line:</strong></p>
-<p>As in the lines above, use the &#8220;-sf opt&#8221; <a class="reference internal" href="Section_start.html#start-7"><span>command-line switch</span></a>, which will automatically append
-&#8220;opt&#8221; to styles that support it.</p>
-<p><strong>Or run with the OPT package by editing an input script:</strong></p>
-<p>Use the <a class="reference internal" href="suffix.html"><em>suffix opt</em></a> command, or you can explicitly add an
-&#8220;opt&#8221; suffix to individual styles in your input script, e.g.</p>
-<div class="highlight-python"><div class="highlight"><pre>pair_style lj/cut/opt 2.5
-</pre></div>
-</div>
-<p><strong>Speed-ups to expect:</strong></p>
-<p>You should see a reduction in the &#8220;Pair time&#8221; value printed at the end
-of a run.  On most machines for reasonable problem sizes, it will be a
-5 to 20% savings.</p>
-<p><strong>Guidelines for best performance:</strong></p>
-<p>Just try out an OPT pair style to see how it performs.</p>
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>None.</p>
-</div>
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doc/angle_charmm.html

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-<li class="toctree-l1"><a class="reference internal" href="Section_intro.html">1. Introduction</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_start.html">2. Getting Started</a></li>
-<li class="toctree-l1"><a class="reference internal" href="Section_commands.html">3. Commands</a></li>
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-  <div class="section" id="angle-style-charmm-command">
-<span id="index-0"></span><h1>angle_style charmm command<a class="headerlink" href="#angle-style-charmm-command" title="Permalink to this headline">¶</a></h1>
-</div>
-<div class="section" id="angle-style-charmm-kk-command">
-<h1>angle_style charmm/kk command<a class="headerlink" href="#angle-style-charmm-kk-command" title="Permalink to this headline">¶</a></h1>
-</div>
-<div class="section" id="angle-style-charmm-omp-command">
-<h1>angle_style charmm/omp command<a class="headerlink" href="#angle-style-charmm-omp-command" title="Permalink to this headline">¶</a></h1>
-<div class="section" id="syntax">
-<h2>Syntax<a class="headerlink" href="#syntax" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-python"><div class="highlight"><pre>angle_style charmm
-</pre></div>
-</div>
-</div>
-<div class="section" id="examples">
-<h2>Examples<a class="headerlink" href="#examples" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-python"><div class="highlight"><pre>angle_style charmm
-angle_coeff 1 300.0 107.0 50.0 3.0
-</pre></div>
-</div>
-</div>
-<div class="section" id="description">
-<h2>Description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h2>
-<p>The <em>charmm</em> angle style uses the potential</p>
-<img alt="_images/angle_charmm.jpg" class="align-center" src="_images/angle_charmm.jpg" />
-<p>with an additional Urey_Bradley term based on the distance <em>r</em> between
-the 1st and 3rd atoms in the angle.  K, theta0, Kub, and Rub are
-coefficients defined for each angle type.</p>
-<p>See <a class="reference internal" href="special_bonds.html#mackerell"><span>(MacKerell)</span></a> for a description of the CHARMM force
-field.</p>
-<p>The following coefficients must be defined for each angle type via the
-<a class="reference internal" href="angle_coeff.html"><em>angle_coeff</em></a> command as in the example above, or in
-the data file or restart files read by the <a class="reference internal" href="read_data.html"><em>read_data</em></a>
-or <a class="reference internal" href="read_restart.html"><em>read_restart</em></a> commands:</p>
-<ul class="simple">
-<li>K (energy/radian^2)</li>
-<li>theta0 (degrees)</li>
-<li>K_ub (energy/distance^2)</li>
-<li>r_ub (distance)</li>
-</ul>
-<p>Theta0 is specified in degrees, but LAMMPS converts it to radians
-internally; hence the units of K are in energy/radian^2.</p>
-<hr class="docutils" />
-<p>Styles with a <em>cuda</em>, <em>gpu</em>, <em>intel</em>, <em>kk</em>, <em>omp</em>, or <em>opt</em> suffix are
-functionally the same as the corresponding style without the suffix.
-They have been optimized to run faster, depending on your available
-hardware, as discussed in <a class="reference internal" href="Section_accelerate.html"><em>Section_accelerate</em></a>
-of the manual.  The accelerated styles take the same arguments and
-should produce the same results, except for round-off and precision
-issues.</p>
-<p>These accelerated styles are part of the USER-CUDA, GPU, USER-INTEL,
-KOKKOS, USER-OMP and OPT packages, respectively.  They are only
-enabled if LAMMPS was built with those packages.  See the <a class="reference internal" href="Section_start.html#start-3"><span>Making LAMMPS</span></a> section for more info.</p>
-<p>You can specify the accelerated styles explicitly in your input script
-by including their suffix, or you can use the <a class="reference internal" href="Section_start.html#start-7"><span>-suffix command-line switch</span></a> when you invoke LAMMPS, or you can
-use the <a class="reference internal" href="suffix.html"><em>suffix</em></a> command in your input script.</p>
-<p>See <a class="reference internal" href="Section_accelerate.html"><em>Section_accelerate</em></a> of the manual for
-more instructions on how to use the accelerated styles effectively.</p>
-</div>
-<hr class="docutils" />
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>This angle style can only be used if LAMMPS was built with the
-MOLECULE package (which it is by default).  See the <a class="reference internal" href="Section_start.html#start-3"><span>Making LAMMPS</span></a> section for more info on packages.</p>
-</div>
-<div class="section" id="related-commands">
-<h2>Related commands<a class="headerlink" href="#related-commands" title="Permalink to this headline">¶</a></h2>
-<p><a class="reference internal" href="angle_coeff.html"><em>angle_coeff</em></a></p>
-<p><strong>Default:</strong> none</p>
-<hr class="docutils" />
-<p id="mackerell"><strong>(MacKerell)</strong> MacKerell, Bashford, Bellott, Dunbrack, Evanseck, Field,
-Fischer, Gao, Guo, Ha, et al, J Phys Chem, 102, 3586 (1998).</p>
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-  <div class="section" id="angle-style-class2-command">
-<span id="index-0"></span><h1>angle_style class2 command<a class="headerlink" href="#angle-style-class2-command" title="Permalink to this headline">¶</a></h1>
-</div>
-<div class="section" id="angle-style-class2-omp-command">
-<h1>angle_style class2/omp command<a class="headerlink" href="#angle-style-class2-omp-command" title="Permalink to this headline">¶</a></h1>
-<div class="section" id="syntax">
-<h2>Syntax<a class="headerlink" href="#syntax" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-python"><div class="highlight"><pre>angle_style class2
-</pre></div>
-</div>
-</div>
-<div class="section" id="examples">
-<h2>Examples<a class="headerlink" href="#examples" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-python"><div class="highlight"><pre>angle_style class2
-angle_coeff * 75.0
-angle_coeff 1 bb 10.5872 1.0119 1.5228
-angle_coeff * ba 3.6551 24.895 1.0119 1.5228
-</pre></div>
-</div>
-</div>
-<div class="section" id="description">
-<h2>Description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h2>
-<p>The <em>class2</em> angle style uses the potential</p>
-<img alt="_images/angle_class2.jpg" class="align-center" src="_images/angle_class2.jpg" />
-<p>where Ea is the angle term, Ebb is a bond-bond term, and Eba is a
-bond-angle term.  Theta0 is the equilibrium angle and r1 and r2 are
-the equilibrium bond lengths.</p>
-<p>See <a class="reference internal" href="pair_modify.html#sun"><span>(Sun)</span></a> for a description of the COMPASS class2 force field.</p>
-<p>Coefficients for the Ea, Ebb, and Eba formulas must be defined for
-each angle type via the <a class="reference internal" href="angle_coeff.html"><em>angle_coeff</em></a> command as in
-the example above, or in the data file or restart files read by the
-<a class="reference internal" href="read_data.html"><em>read_data</em></a> or <a class="reference internal" href="read_restart.html"><em>read_restart</em></a>
-commands.</p>
-<p>These are the 4 coefficients for the Ea formula:</p>
-<ul class="simple">
-<li>theta0 (degrees)</li>
-<li>K2 (energy/radian^2)</li>
-<li>K3 (energy/radian^3)</li>
-<li>K4 (energy/radian^4)</li>
-</ul>
-<p>Theta0 is specified in degrees, but LAMMPS converts it to radians
-internally; hence the units of the various K are in per-radian.</p>
-<p>For the Ebb formula, each line in a <a class="reference internal" href="angle_coeff.html"><em>angle_coeff</em></a>
-command in the input script lists 4 coefficients, the first of which
-is &#8220;bb&#8221; to indicate they are BondBond coefficients.  In a data file,
-these coefficients should be listed under a &#8220;BondBond Coeffs&#8221; heading
-and you must leave out the &#8220;bb&#8221;, i.e. only list 3 coefficients after
-the angle type.</p>
-<ul class="simple">
-<li>bb</li>
-<li>M (energy/distance^2)</li>
-<li>r1 (distance)</li>
-<li>r2 (distance)</li>
-</ul>
-<p>For the Eba formula, each line in a <a class="reference internal" href="angle_coeff.html"><em>angle_coeff</em></a>
-command in the input script lists 5 coefficients, the first of which
-is &#8220;ba&#8221; to indicate they are BondAngle coefficients.  In a data file,
-these coefficients should be listed under a &#8220;BondAngle Coeffs&#8221; heading
-and you must leave out the &#8220;ba&#8221;, i.e. only list 4 coefficients after
-the angle type.</p>
-<ul class="simple">
-<li>ba</li>
-<li>N1 (energy/distance^2)</li>
-<li>N2 (energy/distance^2)</li>
-<li>r1 (distance)</li>
-<li>r2 (distance)</li>
-</ul>
-<p>The theta0 value in the Eba formula is not specified, since it is the
-same value from the Ea formula.</p>
-<hr class="docutils" />
-<p>Styles with a <em>cuda</em>, <em>gpu</em>, <em>intel</em>, <em>kk</em>, <em>omp</em>, or <em>opt</em> suffix are
-functionally the same as the corresponding style without the suffix.
-They have been optimized to run faster, depending on your available
-hardware, as discussed in <a class="reference internal" href="Section_accelerate.html"><em>Section_accelerate</em></a>
-of the manual.  The accelerated styles take the same arguments and
-should produce the same results, except for round-off and precision
-issues.</p>
-<p>These accelerated styles are part of the USER-CUDA, GPU, USER-INTEL,
-KOKKOS, USER-OMP and OPT packages, respectively.  They are only
-enabled if LAMMPS was built with those packages.  See the <a class="reference internal" href="Section_start.html#start-3"><span>Making LAMMPS</span></a> section for more info.</p>
-<p>You can specify the accelerated styles explicitly in your input script
-by including their suffix, or you can use the <a class="reference internal" href="Section_start.html#start-7"><span>-suffix command-line switch</span></a> when you invoke LAMMPS, or you can
-use the <a class="reference internal" href="suffix.html"><em>suffix</em></a> command in your input script.</p>
-<p>See <a class="reference internal" href="Section_accelerate.html"><em>Section_accelerate</em></a> of the manual for
-more instructions on how to use the accelerated styles effectively.</p>
-</div>
-<hr class="docutils" />
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>This angle style can only be used if LAMMPS was built with the CLASS2
-package.  See the <a class="reference internal" href="Section_start.html#start-3"><span>Making LAMMPS</span></a> section
-for more info on packages.</p>
-</div>
-<div class="section" id="related-commands">
-<h2>Related commands<a class="headerlink" href="#related-commands" title="Permalink to this headline">¶</a></h2>
-<p><a class="reference internal" href="angle_coeff.html"><em>angle_coeff</em></a></p>
-<p><strong>Default:</strong> none</p>
-<hr class="docutils" />
-<p id="sun"><strong>(Sun)</strong> Sun, J Phys Chem B 102, 7338-7364 (1998).</p>
-</div>
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-  <div class="section" id="angle-coeff-command">
-<span id="index-0"></span><h1>angle_coeff command<a class="headerlink" href="#angle-coeff-command" title="Permalink to this headline">¶</a></h1>
-<div class="section" id="syntax">
-<h2>Syntax<a class="headerlink" href="#syntax" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-python"><div class="highlight"><pre>angle_coeff N args
-</pre></div>
-</div>
-<ul class="simple">
-<li>N = angle type (see asterisk form below)</li>
-<li>args = coefficients for one or more angle types</li>
-</ul>
-</div>
-<div class="section" id="examples">
-<h2>Examples<a class="headerlink" href="#examples" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-python"><div class="highlight"><pre>angle_coeff 1 300.0 107.0
-angle_coeff * 5.0
-angle_coeff 2*10 5.0
-</pre></div>
-</div>
-</div>
-<div class="section" id="description">
-<h2>Description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h2>
-<p>Specify the angle force field coefficients for one or more angle types.
-The number and meaning of the coefficients depends on the angle style.
-Angle coefficients can also be set in the data file read by the
-<a class="reference internal" href="read_data.html"><em>read_data</em></a> command or in a restart file.</p>
-<p>N can be specified in one of two ways.  An explicit numeric value can
-be used, as in the 1st example above.  Or a wild-card asterisk can be
-used to set the coefficients for multiple angle types.  This takes the
-form &#8220;*&#8221; or &#8220;<em>n&#8221; or &#8220;n</em>&#8221; or &#8220;m*n&#8221;.  If N = the number of angle types,
-then an asterisk with no numeric values means all types from 1 to N.  A
-leading asterisk means all types from 1 to n (inclusive).  A trailing
-asterisk means all types from n to N (inclusive).  A middle asterisk
-means all types from m to n (inclusive).</p>
-<p>Note that using an angle_coeff command can override a previous setting
-for the same angle type.  For example, these commands set the coeffs
-for all angle types, then overwrite the coeffs for just angle type 2:</p>
-<div class="highlight-python"><div class="highlight"><pre>angle_coeff * 200.0 107.0 1.2
-angle_coeff 2 50.0 107.0
-</pre></div>
-</div>
-<p>A line in a data file that specifies angle coefficients uses the exact
-same format as the arguments of the angle_coeff command in an input
-script, except that wild-card asterisks should not be used since
-coefficients for all N types must be listed in the file.  For example,
-under the &#8220;Angle Coeffs&#8221; section of a data file, the line that
-corresponds to the 1st example above would be listed as</p>
-<div class="highlight-python"><div class="highlight"><pre>1 300.0 107.0
-</pre></div>
-</div>
-<p>The <a class="reference internal" href="angle_class2.html"><em>angle_style class2</em></a> is an exception to this
-rule, in that an additional argument is used in the input script to
-allow specification of the cross-term coefficients.   See its
-doc page for details.</p>
-<hr class="docutils" />
-<p>Here is an alphabetic list of angle styles defined in LAMMPS.  Click on
-the style to display the formula it computes and coefficients
-specified by the associated <a class="reference internal" href=""><em>angle_coeff</em></a> command.</p>
-<p>Note that there are also additional angle styles submitted by users
-which are included in the LAMMPS distribution.  The list of these with
-links to the individual styles are given in the angle section of <a class="reference internal" href="Section_commands.html#cmd-5"><span>this page</span></a>.</p>
-<ul class="simple">
-<li><a class="reference internal" href="angle_none.html"><em>angle_style none</em></a> - turn off angle interactions</li>
-<li><a class="reference internal" href="angle_hybrid.html"><em>angle_style hybrid</em></a> - define multiple styles of angle interactions</li>
-<li><a class="reference internal" href="angle_charmm.html"><em>angle_style charmm</em></a> - CHARMM angle</li>
-<li><a class="reference internal" href="angle_class2.html"><em>angle_style class2</em></a> - COMPASS (class 2) angle</li>
-<li><a class="reference internal" href="angle_cosine.html"><em>angle_style cosine</em></a> - cosine angle potential</li>
-<li><a class="reference internal" href="angle_cosine_delta.html"><em>angle_style cosine/delta</em></a> - difference of cosines angle potential</li>
-<li><a class="reference internal" href="angle_cosine_periodic.html"><em>angle_style cosine/periodic</em></a> - DREIDING angle</li>
-<li><a class="reference internal" href="angle_cosine_squared.html"><em>angle_style cosine/squared</em></a> - cosine squared angle potential</li>
-<li><a class="reference internal" href="angle_harmonic.html"><em>angle_style harmonic</em></a> - harmonic angle</li>
-<li><a class="reference internal" href="angle_table.html"><em>angle_style table</em></a> - tabulated by angle</li>
-</ul>
-</div>
-<hr class="docutils" />
-<div class="section" id="restrictions">
-<h2>Restrictions<a class="headerlink" href="#restrictions" title="Permalink to this headline">¶</a></h2>
-<p>This command must come after the simulation box is defined by a
-<a class="reference internal" href="read_data.html"><em>read_data</em></a>, <a class="reference internal" href="read_restart.html"><em>read_restart</em></a>, or
-<a class="reference internal" href="create_box.html"><em>create_box</em></a> command.</p>
-<p>An angle style must be defined before any angle coefficients are
-set, either in the input script or in a data file.</p>
-</div>
-<div class="section" id="related-commands">
-<h2>Related commands<a class="headerlink" href="#related-commands" title="Permalink to this headline">¶</a></h2>
-<p><a class="reference internal" href="angle_style.html"><em>angle_style</em></a></p>
-<p><strong>Default:</strong> none</p>
-</div>
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