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lammps/lib/gpu/lj_gpu.cu

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/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
Copyright (2003) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the GNU General Public License.
See the README file in the top-level LAMMPS directory.
------------------------------------------------------------------------- */
/* ----------------------------------------------------------------------
Contributing authors: Mike Brown (SNL), wmbrown@sandia.gov
Peng Wang (Nvidia), penwang@nvidia.com
Paul Crozier (SNL), pscrozi@sandia.gov
------------------------------------------------------------------------- */
#include <iostream>
#include <cassert>
#include "nvc_macros.h"
#include "nvc_timer.h"
#include "nvc_device.h"
#include "pair_gpu_texture.h"
#include "pair_gpu_cell.h"
#include "lj_gpu_memory.cu"
#include "lj_gpu_kernel.h"
static LJ_GPU_Memory<PRECISION,ACC_PRECISION> LJMF;
#define LJMT LJ_GPU_Memory<numtyp,acctyp>
// ---------------------------------------------------------------------------
// Convert something to a string
// ---------------------------------------------------------------------------
#include <sstream>
template <class t>
inline string lj_gpu_toa(const t& in) {
ostringstream o;
o.precision(2);
o << in;
return o.str();
}
// ---------------------------------------------------------------------------
// Return string with GPU info
// ---------------------------------------------------------------------------
EXTERN void lj_gpu_name(const int id, const int max_nbors, char * name) {
string sname=LJMF.gpu.name(id)+", "+
lj_gpu_toa(LJMF.gpu.cores(id))+" cores, "+
lj_gpu_toa(LJMF.gpu.gigabytes(id))+" GB, "+
lj_gpu_toa(LJMF.gpu.clock_rate(id))+" GHZ";
strcpy(name,sname.c_str());
}
// ---------------------------------------------------------------------------
// Allocate memory on host and device and copy constants to device
// ---------------------------------------------------------------------------
EXTERN bool lj_gpu_init(int &ij_size, const int ntypes, double **cutsq,double **sigma,
double **epsilon, double **host_lj1, double **host_lj2,
double **host_lj3, double **host_lj4, double **offset,
double *special_lj, double *boxlo, double *boxhi,
double cell_size, double skin,
const int max_nbors, const int gpu_id) {
LJMF.gpu.init();
if (LJMF.gpu.num_devices()==0)
return false;
ij_size=IJ_SIZE;
bool ret = LJMF.init(ij_size, ntypes, cutsq, sigma, epsilon, host_lj1, host_lj2,
host_lj3, host_lj4, offset, special_lj, max_nbors, gpu_id);
ncellx = ceil(((boxhi[0] - boxlo[0]) + 2.0*cell_size) / cell_size);
ncelly = ceil(((boxhi[1] - boxlo[1]) + 2.0*cell_size) / cell_size);
ncellz = ceil(((boxhi[2] - boxlo[2]) + 2.0*cell_size) / cell_size);
init_cell_list_const(cell_size, skin, boxlo, boxhi);
return ret;
}
// ---------------------------------------------------------------------------
// Clear memory on host and device
// ---------------------------------------------------------------------------
EXTERN void lj_gpu_clear() {
free(energy);
free(v_temp);
cudaFreeHost(f_temp);
cudaFree(d_force);
cudaFree(d_energy);
cudaFree(d_virial);
clear_cell_list(cell_list_gpu);
LJMF.clear();
}
// ---------------------------------------------------------------------------
// Calculate energies and forces for all ij interactions
// ---------------------------------------------------------------------------
template <class numtyp, class acctyp>
void _lj_gpu(LJMT &ljm, const bool eflag, const bool vflag, const bool rebuild){
// Compute the block size and grid size to keep all cores busy
const int BX=BLOCK_1D;
int GX=static_cast<int>(ceil(static_cast<double>(ljm.atom.inum())/BX));
ljm.time_pair.start();
if (ljm.shared_types)
kernel_lj_fast<numtyp,acctyp><<<GX,BX,0,ljm.pair_stream>>>
(ljm.special_lj.begin(), ljm.nbor.dev_nbor.begin(),
ljm.nbor.ij.begin(), ljm.nbor.dev_nbor.row_size(),
ljm.atom.ans.begin(), ljm.atom.ans.row_size(), eflag,
vflag, ljm.atom.inum(), ljm.atom.nall());
else
kernel_lj<numtyp,acctyp><<<GX,BX,0,ljm.pair_stream>>>
(ljm.special_lj.begin(), ljm.nbor.dev_nbor.begin(),
ljm.nbor.ij.begin(), ljm.nbor.dev_nbor.row_size(),
ljm.atom.ans.begin(), ljm.atom.ans.row_size(), eflag,
vflag, ljm.atom.inum(), ljm.atom.nall());
ljm.time_pair.stop();
}
EXTERN void lj_gpu(const bool eflag, const bool vflag, const bool rebuild) {
_lj_gpu<PRECISION,ACC_PRECISION>(LJMF, eflag,vflag,rebuild);
}
template <class numtyp, class acctyp>
double _lj_gpu_cell(LJMT &ljm, double **force, double *virial,
double **host_x, int *host_type, const int inum,
const int nall, const int ago, const bool eflag, const bool vflag,
const double *boxlo, const double *boxhi)
{
cudaError_t err;
ljm.atom.nall(nall);
ljm.atom.inum(inum);
ljm.nbor.time_nbor.start();
ljm.nbor.time_nbor.stop();
double evdwl=0.0;
static int blockSize = BLOCK_1D;
static int ncell = ncellx*ncelly*ncellz;
static int first_call = 1;
// allocate memory on CPU and GPU
if (first_call) {
energy = (float*) malloc(inum*sizeof(float));
v_temp = (float3*)malloc(inum*2*sizeof(float3));
cudaMallocHost((void**)&f_temp, inum*sizeof(float3));
cudaMalloc((void**)&d_force, inum*sizeof(float3));
cudaMalloc((void**)&d_energy, inum*sizeof(float));
cudaMalloc((void**)&d_virial, inum*3*sizeof(float3));
init_cell_list(cell_list_gpu, nall, ncell, blockSize);
first_call = 0;
}
if (!first_call && ago == 0) {
free(energy);
free(v_temp);
cudaFreeHost(f_temp);
cudaFree(d_force);
cudaFree(d_energy);
cudaFree(d_virial);
energy = (float*) malloc(inum*sizeof(float));
v_temp = (float3*)malloc(inum*2*sizeof(float3));
cudaMallocHost((void**)&f_temp, inum*sizeof(float3));
cudaMalloc((void**)&d_force, inum*sizeof(float3));
cudaMalloc((void**)&d_energy, inum*sizeof(float));
cudaMalloc((void**)&d_virial, inum*3*sizeof(float3));
clear_cell_list(cell_list_gpu);
init_cell_list(cell_list_gpu, nall, ncell, blockSize);
}
// build cell-list on GPU
ljm.atom.time_atom.start();
build_cell_list(host_x[0], host_type, cell_list_gpu,
ncell, ncellx, ncelly, ncellz, blockSize, inum, nall, ago);
ljm.atom.time_atom.stop();
ljm.time_pair.start();
#ifdef TIMING
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
cudaEventRecord(start, 0);
#endif
#define KERNEL_LJ_CELL(e, v, b, s) kernel_lj_cell<e,v,b><<<GX, BX, s>>> \
(d_force, d_energy, d_virial, \
cell_list_gpu.pos, \
cell_list_gpu.idx, \
cell_list_gpu.type, \
cell_list_gpu.natom, \
inum, nall, ncell, ncellx, ncelly, ncellz);
// call the cell-list force kernel
const int BX=blockSize;
dim3 GX(ncellx, ncelly*ncellz);
if (eflag == 0 && vflag == 0) {
if (blockSize == 64 ) KERNEL_LJ_CELL(false, false, 64, 0);
if (blockSize == 128) KERNEL_LJ_CELL(false, false, 128, 0);
if (blockSize == 256) KERNEL_LJ_CELL(false, false, 256, 0);
} else {
if (blockSize == 64) KERNEL_LJ_CELL(true, true, 64, 3*sizeof(float)*MAX_SHARED_TYPES*MAX_SHARED_TYPES);
if (blockSize == 128) KERNEL_LJ_CELL(true, true, 128, 3*sizeof(float)*MAX_SHARED_TYPES*MAX_SHARED_TYPES);
if (blockSize == 256) KERNEL_LJ_CELL(true, true, 256, 3*sizeof(float)*MAX_SHARED_TYPES*MAX_SHARED_TYPES);
}
err = cudaGetLastError();
if (err != cudaSuccess) {
printf("LJ force kernel launch error: %d\n", err);
exit(1);
}
#ifdef TIMING
cudaEventRecord(stop, 0);
cudaEventSynchronize(stop);
float kTime;
cudaEventElapsedTime(&kTime, start, stop);
kernelTime += kTime;
printf("kernelTime = %f, eflag=%d, vflag=%d\n", kTime, eflag, vflag);
cudaEventDestroy(start);
cudaEventDestroy(stop);
#endif
// copy results from GPU to CPU
cudaMemcpy(f_temp, d_force, inum*sizeof(float3), cudaMemcpyDeviceToHost);
if (eflag) {
cudaMemcpy(energy, d_energy, inum*sizeof(float), cudaMemcpyDeviceToHost);
for (int i = 0; i < inum; i++) {
evdwl += energy[i];
}
evdwl *= 0.5f;
}
if (vflag) {
cudaMemcpy(v_temp, d_virial, inum*2*sizeof(float3), cudaMemcpyDeviceToHost);
for (int i = 0; i < inum; i++) {
virial[0] += v_temp[2*i].x;
virial[1] += v_temp[2*i].y;
virial[2] += v_temp[2*i].z;
virial[3] += v_temp[2*i+1].x;
virial[4] += v_temp[2*i+1].y;
virial[5] += v_temp[2*i+1].z;
}
for (int i = 0; i < 6; i++)
virial[i] *= 0.5f;
}
for (int i = 0; i < inum; i++) {
force[i][0] += f_temp[i].x;
force[i][1] += f_temp[i].y;
force[i][2] += f_temp[i].z;
}
ljm.time_pair.stop();
ljm.atom.time_atom.add_to_total();
ljm.nbor.time_nbor.add_to_total();
ljm.time_pair.add_to_total();
return evdwl;
}
EXTERN double lj_gpu_cell(double **force, double *virial, double **host_x, int *host_type, const int inum, const int nall,
const int ago, const bool eflag, const bool vflag,
const double *boxlo, const double *boxhi)
{
return _lj_gpu_cell<PRECISION,ACC_PRECISION>(LJMF, force, virial, host_x, host_type, inum, nall,
ago, eflag, vflag, boxlo, boxhi);
}
EXTERN void lj_gpu_time() {
cout.precision(4);
cout << "Atom copy: " << LJMF.atom.time_atom.total_seconds() << " s.\n";
cout << "Neighbor copy: " << LJMF.nbor.time_nbor.total_seconds() << " s.\n";
cout << "LJ calc: " << LJMF.time_pair.total_seconds() << " s.\n";
cout << "Answer copy: " << LJMF.atom.time_answer.total_seconds() << " s.\n";
}
EXTERN int lj_gpu_num_devices() {
return LJMF.gpu.num_devices();
}
EXTERN double lj_gpu_bytes() {
return LJMF.host_memory_usage();
}
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