ICODE-ADC/lammps
4
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@8922 f3b2605a-c512-4ea7-a41b-209d697bcdaa

Browse Source
This commit is contained in:
sjplimp
2012-10-08 15:29:55 +00:00
parent 856a237400
commit 14bcb1e6d0
184 changed files with 23096 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

161
lib/cuda/compute_temp_partial_cuda_kernel.cu Normal file
View File

@ -0,0 +1,161 @@
/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
Original Version:
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
See the README file in the top-level LAMMPS directory.
-----------------------------------------------------------------------
USER-CUDA Package and associated modifications:
https://sourceforge.net/projects/lammpscuda/
Christian Trott, christian.trott@tu-ilmenau.de
Lars Winterfeld, lars.winterfeld@tu-ilmenau.de
Theoretical Physics II, University of Technology Ilmenau, Germany
See the README file in the USER-CUDA directory.
This software is distributed under the GNU General Public License.
------------------------------------------------------------------------- */
extern __shared__ ENERGY_FLOAT sharedmem[];
__global__ void Cuda_ComputeTempPartialCuda_Scalar_Kernel(int groupbit, int xflag, int yflag, int zflag)
{
int i = (blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x;
sharedmem[threadIdx.x] = 0;
if(i < _nlocal) {
if(_rmass_flag) {
if(_mask[i] & groupbit)
sharedmem[threadIdx.x] = (_v[i] * _v[i] * xflag + _v[i + _nmax] * _v[i + _nmax] * yflag + _v[i + 2 * _nmax] * _v[i + 2 * _nmax] * zflag) * _rmass[i];
} else {
if(_mask[i] & groupbit)
sharedmem[threadIdx.x] = (_v[i] * _v[i] * xflag + _v[i + _nmax] * _v[i + _nmax] * yflag + _v[i + 2 * _nmax] * _v[i + 2 * _nmax] * zflag) * (_mass[_type[i]]);
}
}
reduceBlock(sharedmem);
ENERGY_FLOAT* buffer = (ENERGY_FLOAT*) _buffer;
if(threadIdx.x == 0) {
buffer[blockIdx.x * gridDim.y + blockIdx.y] = sharedmem[0];
}
}
__global__ void Cuda_ComputeTempPartialCuda_Vector_Kernel(int groupbit, int xflag, int yflag, int zflag)
{
int i = (blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x;
sharedmem[threadIdx.x] = 0;
sharedmem[threadIdx.x + blockDim.x] = 0;
sharedmem[threadIdx.x + 2 * blockDim.x] = 0;
sharedmem[threadIdx.x + 3 * blockDim.x] = 0;
sharedmem[threadIdx.x + 4 * blockDim.x] = 0;
sharedmem[threadIdx.x + 5 * blockDim.x] = 0;
if(i < _nlocal)
if(_mask[i] & groupbit) {
V_FLOAT massone;
if(_rmass_flag) massone = _rmass[i];
else massone = _mass[_type[i]];
sharedmem[threadIdx.x] = massone * _v[i] * _v[i] * xflag;
sharedmem[threadIdx.x + blockDim.x] = massone * _v[i + _nmax] * _v[i + _nmax] * yflag;
sharedmem[threadIdx.x + 2 * blockDim.x] = massone * _v[i + 2 * _nmax] * _v[i + 2 * _nmax] * zflag;
sharedmem[threadIdx.x + 3 * blockDim.x] = massone * _v[i] * _v[i + _nmax] * xflag * yflag;
sharedmem[threadIdx.x + 4 * blockDim.x] = massone * _v[i] * _v[i + 2 * _nmax] * xflag * zflag;
sharedmem[threadIdx.x + 5 * blockDim.x] = massone * _v[i + _nmax] * _v[i + 2 * _nmax] * yflag * zflag;
}
reduceBlock(sharedmem);
reduceBlock(&sharedmem[blockDim.x]);
reduceBlock(&sharedmem[2 * blockDim.x]);
reduceBlock(&sharedmem[3 * blockDim.x]);
reduceBlock(&sharedmem[4 * blockDim.x]);
reduceBlock(&sharedmem[5 * blockDim.x]);
ENERGY_FLOAT* buffer = (ENERGY_FLOAT*) _buffer;
if(threadIdx.x == 0) {
buffer[blockIdx.x * gridDim.y + blockIdx.y] = sharedmem[0];
buffer[blockIdx.x * gridDim.y + blockIdx.y + gridDim.x * gridDim.y] = sharedmem[blockDim.x];
buffer[blockIdx.x * gridDim.y + blockIdx.y + 2 * gridDim.x * gridDim.y] = sharedmem[2 * blockDim.x];
buffer[blockIdx.x * gridDim.y + blockIdx.y + 3 * gridDim.x * gridDim.y] = sharedmem[3 * blockDim.x];
buffer[blockIdx.x * gridDim.y + blockIdx.y + 4 * gridDim.x * gridDim.y] = sharedmem[4 * blockDim.x];
buffer[blockIdx.x * gridDim.y + blockIdx.y + 5 * gridDim.x * gridDim.y] = sharedmem[5 * blockDim.x];
}
}
__global__ void Cuda_ComputeTempPartialCuda_Reduce_Kernel(int n, ENERGY_FLOAT* t)
{
int i = 0;
sharedmem[threadIdx.x] = 0;
ENERGY_FLOAT myforig = 0.0;
ENERGY_FLOAT* buf = (ENERGY_FLOAT*) _buffer;
buf = &buf[blockIdx.x * n];
while(i < n) {
sharedmem[threadIdx.x] = 0;
if(i + threadIdx.x < n)
sharedmem[threadIdx.x] = buf[i + threadIdx.x];
__syncthreads();
reduceBlock(sharedmem);
i += blockDim.x;
if(threadIdx.x == 0)
myforig += sharedmem[0];
}
if(threadIdx.x == 0)
t[blockIdx.x] = myforig;
}
__global__ void Cuda_ComputeTempPartialCuda_RemoveBiasAll_Kernel(int groupbit, int xflag, int yflag, int zflag, V_FLOAT* vbiasall)
{
int i = (blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x;
if(i < _nlocal)
if(_mask[i] & groupbit) {
if(!xflag) {
vbiasall[i] = _v[i];
_v[i] = V_F(0.0);
}
if(!yflag) {
vbiasall[i + _nmax] = _v[i + _nmax];
_v[i + _nmax] = V_F(0.0);
}
if(!zflag) {
vbiasall[i + 2 * _nmax] = _v[i + 2 * _nmax];
_v[i + 2 * _nmax] = V_F(0.0);
}
}
}
__global__ void Cuda_ComputeTempPartialCuda_RestoreBiasAll_Kernel(int groupbit, int xflag, int yflag, int zflag, V_FLOAT* vbiasall)
{
int i = (blockIdx.x * gridDim.y + blockIdx.y) * blockDim.x + threadIdx.x;
if(i < _nlocal)
if(_mask[i] & groupbit) {
if(!xflag) {
_v[i] += vbiasall[i];
}
if(!yflag) {
_v[i + _nmax] += vbiasall[i + _nmax];
}
if(!zflag) {
_v[i + 2 * _nmax] += vbiasall[i + 2 * _nmax];
}
}
}