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remove references to Make.py and USER-CUDA

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Axel Kohlmeyer
2017-07-18 13:24:32 -04:00
parent a351977c59
commit bdd2f3a6b2
4 changed files with 29 additions and 158 deletions
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11
examples/README
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@ -105,20 +105,11 @@ tad: temperature-accelerated dynamics of vacancy diffusion in bulk Si
vashishta: models using the Vashishta potential
voronoi: Voronoi tesselation via compute voronoi/atom command
Here is a src/Make.py command which will perform a parallel build of a
LAMMPS executable "lmp_mpi" with all the packages needed by all the
examples, with the exception of the accelerate sub-directory. See the
accelerate/README for Make.py commands suitable for its example
scripts.
cd src
Make.py -j 16 -p none std no-lib reax meam poems reaxc orig -a lib-all mpi
Here is how you might run and visualize one of the sample problems:
cd indent
cp ../../src/lmp_mpi . # copy LAMMPS executable to this dir
lmp_mpi < in.indent # run the problem
lmp_mpi -in in.indent # run the problem
Running the simulation produces the files {dump.indent} and
{log.lammps}. You can visualize the dump file as follows:

64
examples/accelerate/README
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@ -1,14 +1,11 @@
These are example scripts that can be run with any of
the acclerator packages in LAMMPS:
USER-CUDA, GPU, USER-INTEL, KOKKOS, USER-OMP, OPT
GPU, USER-INTEL, KOKKOS, USER-OMP, OPT
The easiest way to build LAMMPS with these packages
is via the src/Make.py tool described in Section 2.4
of the manual. You can also type "Make.py -h" to see
its options. The easiest way to run these scripts
is by using the appropriate
is via the flags described in Section 4 of the manual.
The easiest way to run these scripts is by using the appropriate
Details on the individual accelerator packages
can be found in doc/Section_accelerate.html.
@ -16,21 +13,6 @@ can be found in doc/Section_accelerate.html.
Build LAMMPS with one or more of the accelerator packages
The following command will invoke the src/Make.py tool with one of the
command-lines from the Make.list file:
../../src/Make.py -r Make.list target
target = one or more of the following:
cpu, omp, opt
cuda_double, cuda_mixed, cuda_single
gpu_double, gpu_mixed, gpu_single
intel_cpu, intel_phi
kokkos_omp, kokkos_cuda, kokkos_phi
If successful, the build will produce the file lmp_target in this
directory.
Note that in addition to any accelerator packages, these packages also
need to be installed to run all of the example scripts: ASPHERE,
MOLECULE, KSPACE, RIGID.
@ -38,39 +20,11 @@ MOLECULE, KSPACE, RIGID.
These two targets will build a single LAMMPS executable with all the
CPU accelerator packages installed (USER-INTEL for CPU, KOKKOS for
OMP, USER-OMP, OPT) or all the GPU accelerator packages installed
(USER-CUDA, GPU, KOKKOS for CUDA):
(GPU, KOKKOS for CUDA):
target = all_cpu, all_gpu
Note that the Make.py commands in Make.list assume an MPI environment
exists on your machine and use mpicxx as the wrapper compiler with
whatever underlying compiler it wraps by default. If you add "-cc mpi
wrap=g++" or "-cc mpi wrap=icc" after the target, you can choose the
underlying compiler for mpicxx to invoke. E.g.
../../src/Make.py -r Make.list intel_cpu -cc mpi wrap=icc
You should do this for any build that includes the USER-INTEL
package, since it will perform best with the Intel compilers.
Note that for kokkos_cuda, it needs to be "-cc nvcc" instead of "mpi",
since a KOKKOS for CUDA build requires NVIDIA nvcc as the wrapper
compiler.
Also note that the Make.py commands in Make.list use the default
FFT support which is via the KISS library. If you want to
build with another FFT library, e.g. FFTW3, then you can add
"-fft fftw3" after the target, e.g.
../../src/Make.py -r Make.list gpu -fft fftw3
For any build with USER-CUDA, GPU, or KOKKOS for CUDA, be sure to set
For any build with GPU, or KOKKOS for CUDA, be sure to set
the arch=XX setting to the appropriate value for the GPUs and Cuda
environment on your system. What is defined in the Make.list file is
arch=21 for older Fermi GPUs. This can be overridden as follows,
e.g. for Kepler GPUs:
../../src/Make.py -r Make.list gpu_double -gpu mode=double arch=35
environment on your system.
---------------------
@ -118,12 +72,6 @@ Note that when running in.lj.5.0 (which has a long cutoff) with the
GPU package, the "-pk tpa" setting should be > 1 (e.g. 8) for best
performance.
** USER-CUDA package
lmp_machine -c on -sf cuda < in.lj
mpirun -np 1 lmp_machine -c on -sf cuda < in.lj # 1 MPI, 1 MPI/GPU
mpirun -np 2 lmp_machine -c on -sf cuda -pk cuda 2 < in.lj # 2 MPI, 1 MPI/GPU
** KOKKOS package for OMP
lmp_kokkos_omp -k on t 1 -sf kk -pk kokkos neigh half < in.lj