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Integrate GROMACS GPU implementation into master branch

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Signed-off-by: Rafael Ravedutti <rafaelravedutti@gmail.com>
This commit is contained in:
Rafael Ravedutti 2022-11-08 18:33:23 +01:00
parent 493915fe95
commit c70ebce4c1
9 changed files with 480 additions and 84 deletions
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18
lammps/device.c → common/device.c
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@ -58,24 +58,6 @@ void memsetGPU(void *d_ptr, int value, size_t bytesize) {
cuda_assert("memsetGPU", cudaMemset(d_ptr, value, bytesize));
}
void initDevice(Atom *atom, Neighbor *neighbor) {
DeviceAtom *d_atom = &(atom->d_atom);
DeviceNeighbor *d_neighbor = &(neighbor->d_neighbor);
d_atom->epsilon = (MD_FLOAT *) allocateGPU(sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
d_atom->sigma6 = (MD_FLOAT *) allocateGPU(sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
d_atom->cutforcesq = (MD_FLOAT *) allocateGPU(sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
d_neighbor->neighbors = (int *) allocateGPU(sizeof(int) * atom->Nmax * neighbor->maxneighs);
d_neighbor->numneigh = (int *) allocateGPU(sizeof(int) * atom->Nmax);
memcpyToGPU(d_atom->x, atom->x, sizeof(MD_FLOAT) * atom->Nmax * 3);
memcpyToGPU(d_atom->vx, atom->vx, sizeof(MD_FLOAT) * atom->Nmax * 3);
memcpyToGPU(d_atom->sigma6, atom->sigma6, sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
memcpyToGPU(d_atom->epsilon, atom->epsilon, sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
memcpyToGPU(d_atom->cutforcesq, atom->cutforcesq, sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
memcpyToGPU(d_atom->type, atom->type, sizeof(int) * atom->Nmax);
}
#else
void initDevice(Atom *atom, Neighbor *neighbor) {}
void *allocateGPU(size_t bytesize) { return NULL; }

2
lammps/includes/device.h → common/includes/device.h
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@ -4,6 +4,8 @@
* Use of this source code is governed by a LGPL-3.0
* license that can be found in the LICENSE file.
*/
#include <stddef.h>
//---
#include <atom.h>
#include <neighbor.h>

317
gromacs/cuda/force_lj.cu Normal file
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@ -0,0 +1,317 @@
/*
* Copyright (C) 2022 NHR@FAU, University Erlangen-Nuremberg.
* All rights reserved. This file is part of MD-Bench.
* Use of this source code is governed by a LGPL-3.0
* license that can be found in the LICENSE file.
*/
extern "C" {
#include <stdio.h>
//---
#include <cuda.h>
#include <driver_types.h>
//---
#include <likwid-marker.h>
//---
#include <atom.h>
#include <device.h>
#include <neighbor.h>
#include <parameter.h>
#include <stats.h>
#include <timing.h>
#include <util.h>
}
extern "C" {
MD_FLOAT *cuda_cl_x;
MD_FLOAT *cuda_cl_v;
MD_FLOAT *cuda_cl_f;
int *cuda_neighbors;
int *cuda_numneigh;
int *cuda_natoms;
int *natoms;
int *ngatoms;
int *cuda_border_map;
int *cuda_jclusters_natoms;
MD_FLOAT *cuda_bbminx, *cuda_bbmaxx;
MD_FLOAT *cuda_bbminy, *cuda_bbmaxy;
MD_FLOAT *cuda_bbminz, *cuda_bbmaxz;
int *cuda_PBCx, *cuda_PBCy, *cuda_PBCz;
int isReneighboured;
}
extern "C"
void initDevice(Atom *atom, Neighbor *neighbor) {
cuda_assert("cudaDeviceSetup", cudaDeviceReset());
cuda_assert("cudaDeviceSetup", cudaSetDevice(0));
cuda_cl_x = (MD_FLOAT *) allocateGPU(atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
cuda_cl_v = (MD_FLOAT *) allocateGPU(atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
cuda_cl_f = (MD_FLOAT *) allocateGPU(atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
cuda_natoms = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_jclusters_natoms = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_border_map = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_PBCx = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_PBCy = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_PBCz = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_numneigh = (int *) allocateGPU(atom->Nclusters_max * sizeof(int));
cuda_neighbors = (int *) allocateGPU(atom->Nclusters_max * neighbor->maxneighs * sizeof(int));
natoms = (int *) malloc(atom->Nclusters_max);
ngatoms = (int *) malloc(atom->Nclusters_max);
isReneighboured = 1;
}
extern "C"
void copyDataToCUDADevice(Atom *atom) {
memcpyToGPU(cuda_cl_x, atom->cl_x, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
memcpyToGPU(cuda_cl_v, atom->cl_v, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
memcpyToGPU(cuda_cl_f, atom->cl_f, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
for(int ci = 0; ci < atom->Nclusters_local; ci++) {
natoms[ci] = atom->iclusters[ci].natoms;
}
memcpyToGPU(cuda_natoms, natoms, atom->Nclusters_local * sizeof(int));
int jfac = MAX(1, CLUSTER_N / CLUSTER_M);
int ncj = atom->Nclusters_local / jfac;
for(int cg = 0; cg < atom->Nclusters_ghost; cg++) {
const int cj = ncj + cg;
ngatoms[cg] = atom->jclusters[cj].natoms;
}
memcpyToGPU(cuda_jclusters_natoms, ngatoms, atom->Nclusters_ghost * sizeof(int));
memcpyToGPU(cuda_border_map, atom->border_map, atom->Nclusters_ghost * sizeof(int));
memcpyToGPU(cuda_PBCx, atom->PBCx, atom->Nclusters_ghost * sizeof(int));
memcpyToGPU(cuda_PBCy, atom->PBCy, atom->Nclusters_ghost * sizeof(int));
memcpyToGPU(cuda_PBCz, atom->PBCz, atom->Nclusters_ghost * sizeof(int));
}
extern "C"
void copyDataFromCUDADevice(Atom *atom) {
memcpyFromGPU(atom->cl_x, cuda_cl_x, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
memcpyFromGPU(atom->cl_v, cuda_cl_v, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
memcpyFromGPU(atom->cl_f, cuda_cl_f, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
}
extern "C"
void cudaDeviceFree() {
cuda_assert("cudaDeviceFree", cudaFree(cuda_cl_x));
cuda_assert("cudaDeviceFree", cudaFree(cuda_cl_v));
cuda_assert("cudaDeviceFree", cudaFree(cuda_cl_f));
cuda_assert("cudaDeviceFree", cudaFree(cuda_numneigh));
cuda_assert("cudaDeviceFree", cudaFree(cuda_neighbors));
cuda_assert("cudaDeviceFree", cudaFree(cuda_natoms));
cuda_assert("cudaDeviceFree", cudaFree(cuda_border_map));
cuda_assert("cudaDeviceFree", cudaFree(cuda_jclusters_natoms));
cuda_assert("cudaDeviceFree", cudaFree(cuda_PBCx));
cuda_assert("cudaDeviceFree", cudaFree(cuda_PBCy));
cuda_assert("cudaDeviceFree", cudaFree(cuda_PBCz));
free(natoms);
free(ngatoms);
}
__global__ void cudaInitialIntegrate_warp(MD_FLOAT *cuda_cl_x, MD_FLOAT *cuda_cl_v, MD_FLOAT *cuda_cl_f,
int *cuda_natoms,
int Nclusters_local, MD_FLOAT dtforce, MD_FLOAT dt) {
unsigned int ci_pos = blockDim.x * blockIdx.x + threadIdx.x;
if (ci_pos >= Nclusters_local) return;
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci_pos);
MD_FLOAT *ci_x = &cuda_cl_x[ci_vec_base];
MD_FLOAT *ci_v = &cuda_cl_v[ci_vec_base];
MD_FLOAT *ci_f = &cuda_cl_f[ci_vec_base];
for (int cii = 0; cii < cuda_natoms[ci_pos]; cii++) {
ci_v[CL_X_OFFSET + cii] += dtforce * ci_f[CL_X_OFFSET + cii];
ci_v[CL_Y_OFFSET + cii] += dtforce * ci_f[CL_Y_OFFSET + cii];
ci_v[CL_Z_OFFSET + cii] += dtforce * ci_f[CL_Z_OFFSET + cii];
ci_x[CL_X_OFFSET + cii] += dt * ci_v[CL_X_OFFSET + cii];
ci_x[CL_Y_OFFSET + cii] += dt * ci_v[CL_Y_OFFSET + cii];
ci_x[CL_Z_OFFSET + cii] += dt * ci_v[CL_Z_OFFSET + cii];
}
}
__global__ void cudaUpdatePbc_warp(MD_FLOAT *cuda_cl_x, int *cuda_border_map,
int *cuda_jclusters_natoms,
int *cuda_PBCx,
int *cuda_PBCy,
int *cuda_PBCz,
int Nclusters_local,
int Nclusters_ghost,
MD_FLOAT param_xprd,
MD_FLOAT param_yprd,
MD_FLOAT param_zprd) {
unsigned int cg = blockDim.x * blockIdx.x + threadIdx.x;
if (cg >= Nclusters_ghost) return;
int jfac = MAX(1, CLUSTER_N / CLUSTER_M);
int ncj = Nclusters_local / jfac;
MD_FLOAT xprd = param_xprd;
MD_FLOAT yprd = param_yprd;
MD_FLOAT zprd = param_zprd;
const int cj = ncj + cg;
int cj_vec_base = CJ_VECTOR_BASE_INDEX(cj);
int bmap_vec_base = CJ_VECTOR_BASE_INDEX(cuda_border_map[cg]);
MD_FLOAT *cj_x = &cuda_cl_x[cj_vec_base];
MD_FLOAT *bmap_x = &cuda_cl_x[bmap_vec_base];
for(int cjj = 0; cjj < cuda_jclusters_natoms[cg]; cjj++) {
cj_x[CL_X_OFFSET + cjj] = bmap_x[CL_X_OFFSET + cjj] + cuda_PBCx[cg] * xprd;
cj_x[CL_Y_OFFSET + cjj] = bmap_x[CL_Y_OFFSET + cjj] + cuda_PBCy[cg] * yprd;
cj_x[CL_Z_OFFSET + cjj] = bmap_x[CL_Z_OFFSET + cjj] + cuda_PBCz[cg] * zprd;
}
}
__global__ void computeForceLJ_cuda_warp(MD_FLOAT *cuda_cl_x, MD_FLOAT *cuda_cl_f,
int Nclusters_local, int Nclusters_max,
int *cuda_numneigh, int *cuda_neighs, int half_neigh, int maxneighs,
MD_FLOAT cutforcesq, MD_FLOAT sigma6, MD_FLOAT epsilon) {
unsigned int ci_pos = blockDim.x * blockIdx.x + threadIdx.x;
unsigned int cii_pos = blockDim.y * blockIdx.y + threadIdx.y;
unsigned int cjj_pos = blockDim.z * blockIdx.z + threadIdx.z;
if ((ci_pos >= Nclusters_local) || (cii_pos >= CLUSTER_M) || (cjj_pos >= CLUSTER_N)) return;
int ci_cj0 = CJ0_FROM_CI(ci_pos);
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci_pos);
MD_FLOAT *ci_x = &cuda_cl_x[ci_vec_base];
MD_FLOAT *ci_f = &cuda_cl_f[ci_vec_base];
int numneighs = cuda_numneigh[ci_pos];
for(int k = 0; k < numneighs; k++) {
int cj = (&cuda_neighs[ci_pos * maxneighs])[k];
int cj_vec_base = CJ_VECTOR_BASE_INDEX(cj);
MD_FLOAT *cj_x = &cuda_cl_x[cj_vec_base];
MD_FLOAT *cj_f = &cuda_cl_f[cj_vec_base];
MD_FLOAT xtmp = ci_x[CL_X_OFFSET + cii_pos];
MD_FLOAT ytmp = ci_x[CL_Y_OFFSET + cii_pos];
MD_FLOAT ztmp = ci_x[CL_Z_OFFSET + cii_pos];
MD_FLOAT fix = 0;
MD_FLOAT fiy = 0;
MD_FLOAT fiz = 0;
int cond;
#if CLUSTER_M == CLUSTER_N
cond = half_neigh ? (ci_cj0 != cj || cii_pos < cjj_pos) :
(ci_cj0 != cj || cii_pos != cjj_pos);
#elif CLUSTER_M < CLUSTER_N
cond = half_neigh ? (ci_cj0 != cj || cii_pos + CLUSTER_M * (ci_pos & 0x1) < cjj_pos) :
(ci_cj0 != cj || cii_pos + CLUSTER_M * (ci_pos & 0x1) != cjj_pos);
#endif
if(cond) {
MD_FLOAT delx = xtmp - cj_x[CL_X_OFFSET + cjj_pos];
MD_FLOAT dely = ytmp - cj_x[CL_Y_OFFSET + cjj_pos];
MD_FLOAT delz = ztmp - cj_x[CL_Z_OFFSET + cjj_pos];
MD_FLOAT rsq = delx * delx + dely * dely + delz * delz;
if(rsq < cutforcesq) {
MD_FLOAT sr2 = 1.0 / rsq;
MD_FLOAT sr6 = sr2 * sr2 * sr2 * sigma6;
MD_FLOAT force = 48.0 * sr6 * (sr6 - 0.5) * sr2 * epsilon;
if(half_neigh) {
atomicAdd(&cj_f[CL_X_OFFSET + cjj_pos], -delx * force);
atomicAdd(&cj_f[CL_Y_OFFSET + cjj_pos], -dely * force);
atomicAdd(&cj_f[CL_Z_OFFSET + cjj_pos], -delz * force);
}
fix += delx * force;
fiy += dely * force;
fiz += delz * force;
atomicAdd(&ci_f[CL_X_OFFSET + cii_pos], fix);
atomicAdd(&ci_f[CL_Y_OFFSET + cii_pos], fiy);
atomicAdd(&ci_f[CL_Z_OFFSET + cii_pos], fiz);
}
}
}
}
__global__ void cudaFinalIntegrate_warp(MD_FLOAT *cuda_cl_v, MD_FLOAT *cuda_cl_f,
int *cuda_natoms,
int Nclusters_local, MD_FLOAT dtforce) {
unsigned int ci_pos = blockDim.x * blockIdx.x + threadIdx.x;
if (ci_pos >= Nclusters_local) return;
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci_pos);
MD_FLOAT *ci_v = &cuda_cl_v[ci_vec_base];
MD_FLOAT *ci_f = &cuda_cl_f[ci_vec_base];
for (int cii = 0; cii < cuda_natoms[ci_pos]; cii++) {
ci_v[CL_X_OFFSET + cii] += dtforce * ci_f[CL_X_OFFSET + cii];
ci_v[CL_Y_OFFSET + cii] += dtforce * ci_f[CL_Y_OFFSET + cii];
ci_v[CL_Z_OFFSET + cii] += dtforce * ci_f[CL_Z_OFFSET + cii];
}
}
extern "C"
void cudaInitialIntegrate(Parameter *param, Atom *atom) {
const int threads_num = 16;
dim3 block_size = dim3(threads_num, 1, 1);
dim3 grid_size = dim3(atom->Nclusters_local/(threads_num)+1, 1, 1);
cudaInitialIntegrate_warp<<<grid_size, block_size>>>(cuda_cl_x, cuda_cl_v, cuda_cl_f,
cuda_natoms, atom->Nclusters_local, param->dtforce, param->dt);
cuda_assert("cudaInitialIntegrate", cudaPeekAtLastError());
cuda_assert("cudaInitialIntegrate", cudaDeviceSynchronize());
}
/* update coordinates of ghost atoms */
/* uses mapping created in setupPbc */
extern "C"
void cudaUpdatePbc(Atom *atom, Parameter *param) {
const int threads_num = 512;
dim3 block_size = dim3(threads_num, 1, 1);;
dim3 grid_size = dim3(atom->Nclusters_ghost/(threads_num)+1, 1, 1);;
cudaUpdatePbc_warp<<<grid_size, block_size>>>(cuda_cl_x, cuda_border_map,
cuda_jclusters_natoms, cuda_PBCx, cuda_PBCy, cuda_PBCz,
atom->Nclusters_local, atom->Nclusters_ghost,
param->xprd, param->yprd, param->zprd);
cuda_assert("cudaUpdatePbc", cudaPeekAtLastError());
cuda_assert("cudaUpdatePbc", cudaDeviceSynchronize());
}
extern "C"
double computeForceLJ_cuda(Parameter *param, Atom *atom, Neighbor *neighbor, Stats *stats) {
MD_FLOAT cutforcesq = param->cutforce * param->cutforce;
MD_FLOAT sigma6 = param->sigma6;
MD_FLOAT epsilon = param->epsilon;
memsetGPU(cuda_cl_f, 0, atom->Nclusters_max * CLUSTER_M * 3 * sizeof(MD_FLOAT));
if (isReneighboured) {
for(int ci = 0; ci < atom->Nclusters_local; ci++) {
memcpyToGPU(&cuda_numneigh[ci], &neighbor->numneigh[ci], sizeof(int));
memcpyToGPU(&cuda_neighbors[ci * neighbor->maxneighs], &neighbor->neighbors[ci * neighbor->maxneighs], neighbor->numneigh[ci] * sizeof(int));
}
isReneighboured = 0;
}
const int threads_num = 1;
dim3 block_size = dim3(threads_num, CLUSTER_M, CLUSTER_N);
dim3 grid_size = dim3(atom->Nclusters_local/threads_num+1, 1, 1);
double S = getTimeStamp();
LIKWID_MARKER_START("force");
computeForceLJ_cuda_warp<<<grid_size, block_size>>>(cuda_cl_x, cuda_cl_f,
atom->Nclusters_local, atom->Nclusters_max,
cuda_numneigh, cuda_neighbors,
neighbor->half_neigh, neighbor->maxneighs, cutforcesq,
sigma6, epsilon);
cuda_assert("computeForceLJ_cuda", cudaPeekAtLastError());
cuda_assert("computeForceLJ_cuda", cudaDeviceSynchronize());
LIKWID_MARKER_STOP("force");
double E = getTimeStamp();
return E-S;
}
extern "C"
void cudaFinalIntegrate(Parameter *param, Atom *atom) {
const int threads_num = 16;
dim3 block_size = dim3(threads_num, 1, 1);
dim3 grid_size = dim3(atom->Nclusters_local/(threads_num)+1, 1, 1);
cudaFinalIntegrate_warp<<<grid_size, block_size>>>(cuda_cl_v, cuda_cl_f, cuda_natoms, atom->Nclusters_local, param->dt);
cuda_assert("cudaFinalIntegrate", cudaPeekAtLastError());
cuda_assert("cudaFinalIntegrate", cudaDeviceSynchronize());
}

50
gromacs/includes/atom.h
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@ -11,29 +11,43 @@
#define DELTA 20000
#define CLUSTER_M 4
// Nbnxn layouts (as of GROMACS):
// Simd4xN: M=4, N=VECTOR_WIDTH
// Simd2xNN: M=4, N=(VECTOR_WIDTH/2)
// Cuda: M=8, N=VECTOR_WIDTH
// Simd2xNN (here used for single-precision)
#if VECTOR_WIDTH > CLUSTER_M * 2
# define KERNEL_NAME "Simd2xNN"
# define CLUSTER_N (VECTOR_WIDTH / 2)
# define computeForceLJ computeForceLJ_2xnn
// Simd4xN
#else
# define KERNEL_NAME "Simd4xN"
#ifdef CUDA_TARGET
# undef VECTOR_WIDTH
# define VECTOR_WIDTH 8
# define KERNEL_NAME "CUDA"
# define CLUSTER_M 8
# define CLUSTER_N VECTOR_WIDTH
# define computeForceLJ computeForceLJ_4xn
#endif
#ifdef USE_REFERENCE_VERSION
# undef KERNEL_NAME
# undef computeForceLJ
# define KERNEL_NAME "Reference"
# define computeForceLJ computeForceLJ_ref
# define computeForceLJ computeForceLJ_cuda
# define initialIntegrate cudaInitialIntegrate
# define finalIntegrate cudaFinalIntegrate
# define updatePbc cudaUpdatePbc
#else
# define CLUSTER_M 4
// Simd2xNN (here used for single-precision)
# if VECTOR_WIDTH > CLUSTER_M * 2
# define KERNEL_NAME "Simd2xNN"
# define CLUSTER_N (VECTOR_WIDTH / 2)
# define computeForceLJ computeForceLJ_2xnn
// Simd4xN
# else
# define KERNEL_NAME "Simd4xN"
# define CLUSTER_N VECTOR_WIDTH
# define computeForceLJ computeForceLJ_4xn
# endif
# ifdef USE_REFERENCE_VERSION
# undef KERNEL_NAME
# undef computeForceLJ
# define KERNEL_NAME "Reference"
# define computeForceLJ computeForceLJ_ref
# endif
# define initialIntegrate cpuInitialIntegrate
# define finalIntegrate cpuFinalIntegrate
# define updatePbc cpuUpdatePbc
#endif
#if CLUSTER_M == CLUSTER_N

56
gromacs/includes/integrate.h Normal file
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@ -0,0 +1,56 @@
/*
* Copyright (C) 2022 NHR@FAU, University Erlangen-Nuremberg.
* All rights reserved. This file is part of MD-Bench.
* Use of this source code is governed by a LGPL-3.0
* license that can be found in the LICENSE file.
*/
#include <stdbool.h>
//---
#include <atom.h>
#include <parameter.h>
#include <util.h>
void cpuInitialIntegrate(Parameter *param, Atom *atom) {
DEBUG_MESSAGE("cpuInitialIntegrate start\n");
for(int ci = 0; ci < atom->Nclusters_local; ci++) {
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci);
MD_FLOAT *ci_x = &atom->cl_x[ci_vec_base];
MD_FLOAT *ci_v = &atom->cl_v[ci_vec_base];
MD_FLOAT *ci_f = &atom->cl_f[ci_vec_base];
for(int cii = 0; cii < atom->iclusters[ci].natoms; cii++) {
ci_v[CL_X_OFFSET + cii] += param->dtforce * ci_f[CL_X_OFFSET + cii];
ci_v[CL_Y_OFFSET + cii] += param->dtforce * ci_f[CL_Y_OFFSET + cii];
ci_v[CL_Z_OFFSET + cii] += param->dtforce * ci_f[CL_Z_OFFSET + cii];
ci_x[CL_X_OFFSET + cii] += param->dt * ci_v[CL_X_OFFSET + cii];
ci_x[CL_Y_OFFSET + cii] += param->dt * ci_v[CL_Y_OFFSET + cii];
ci_x[CL_Z_OFFSET + cii] += param->dt * ci_v[CL_Z_OFFSET + cii];
}
}
DEBUG_MESSAGE("cpuInitialIntegrate end\n");
}
void cpuFinalIntegrate(Parameter *param, Atom *atom) {
DEBUG_MESSAGE("cpuFinalIntegrate start\n");
for(int ci = 0; ci < atom->Nclusters_local; ci++) {
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci);
MD_FLOAT *ci_v = &atom->cl_v[ci_vec_base];
MD_FLOAT *ci_f = &atom->cl_f[ci_vec_base];
for(int cii = 0; cii < atom->iclusters[ci].natoms; cii++) {
ci_v[CL_X_OFFSET + cii] += param->dtforce * ci_f[CL_X_OFFSET + cii];
ci_v[CL_Y_OFFSET + cii] += param->dtforce * ci_f[CL_Y_OFFSET + cii];
ci_v[CL_Z_OFFSET + cii] += param->dtforce * ci_f[CL_Z_OFFSET + cii];
}
}
DEBUG_MESSAGE("cpuFinalIntegrate end\n");
}
#ifdef CUDA_TARGET
void cudaInitialIntegrate(Parameter*, Atom*);
void cudaFinalIntegrate(Parameter*, Atom*);
#endif

6
gromacs/includes/pbc.h
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@ -10,7 +10,11 @@
#ifndef __PBC_H_
#define __PBC_H_
extern void initPbc();
extern void updatePbc(Atom*, Parameter*, int);
extern void cpuUpdatePbc(Atom*, Parameter*, int);
extern void updateAtomsPbc(Atom*, Parameter*);
extern void setupPbc(Atom*, Parameter*);
#ifdef CUDA_TARGET
extern void cudaUpdatePbc(Atom*, Parameter*, int);
#endif
#endif

84
gromacs/main.c
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@ -9,19 +9,21 @@
//--
#include <likwid-marker.h>
//--
#include <timing.h>
#include <atom.h>
#include <allocate.h>
#include <device.h>
#include <eam.h>
#include <integrate.h>
#include <neighbor.h>
#include <parameter.h>
#include <atom.h>
#include <pbc.h>
#include <stats.h>
#include <thermo.h>
#include <pbc.h>
#include <timers.h>
#include <eam.h>
#include <timing.h>
#include <util.h>
#include <vtk.h>
#include <xtc.h>
#include <util.h>
#define HLINE "----------------------------------------------------------------------------\n"
@ -30,6 +32,14 @@ extern double computeForceLJ_4xn(Parameter*, Atom*, Neighbor*, Stats*);
extern double computeForceLJ_2xnn(Parameter*, Atom*, Neighbor*, Stats*);
extern double computeForceEam(Eam*, Parameter*, Atom*, Neighbor*, Stats*);
#ifdef CUDA_TARGET
extern int isReneighboured;
extern double computeForceLJ_cuda(Parameter *param, Atom *atom, Neighbor *neighbor, Stats *stats);
extern void copyDataToCUDADevice(Atom *atom);
extern void copyDataFromCUDADevice(Atom *atom);
extern void cudaDeviceFree();
#endif
double setup(Parameter *param, Eam *eam, Atom *atom, Neighbor *neighbor, Stats *stats) {
if(param->force_field == FF_EAM) { initEam(eam, param); }
double S, E;
@ -43,7 +53,6 @@ double setup(Parameter *param, Eam *eam, Atom *atom, Neighbor *neighbor, Stats *
initPbc(atom);
initStats(stats);
initNeighbor(neighbor, param);
if(param->input_file == NULL) {
createAtom(atom, param);
} else {
@ -56,6 +65,7 @@ double setup(Parameter *param, Eam *eam, Atom *atom, Neighbor *neighbor, Stats *
buildClusters(atom);
defineJClusters(atom);
setupPbc(atom, param);
initDevice(atom, neighbor);
binClusters(atom);
buildNeighbor(atom, neighbor);
E = getTimeStamp();
@ -78,46 +88,6 @@ double reneighbour(Parameter *param, Atom *atom, Neighbor *neighbor) {
return E-S;
}
void initialIntegrate(Parameter *param, Atom *atom) {
DEBUG_MESSAGE("initialIntegrate start\n");
for(int ci = 0; ci < atom->Nclusters_local; ci++) {
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci);
MD_FLOAT *ci_x = &atom->cl_x[ci_vec_base];
MD_FLOAT *ci_v = &atom->cl_v[ci_vec_base];
MD_FLOAT *ci_f = &atom->cl_f[ci_vec_base];
for(int cii = 0; cii < atom->iclusters[ci].natoms; cii++) {
ci_v[CL_X_OFFSET + cii] += param->dtforce * ci_f[CL_X_OFFSET + cii];
ci_v[CL_Y_OFFSET + cii] += param->dtforce * ci_f[CL_Y_OFFSET + cii];
ci_v[CL_Z_OFFSET + cii] += param->dtforce * ci_f[CL_Z_OFFSET + cii];
ci_x[CL_X_OFFSET + cii] += param->dt * ci_v[CL_X_OFFSET + cii];
ci_x[CL_Y_OFFSET + cii] += param->dt * ci_v[CL_Y_OFFSET + cii];
ci_x[CL_Z_OFFSET + cii] += param->dt * ci_v[CL_Z_OFFSET + cii];
}
}
DEBUG_MESSAGE("initialIntegrate end\n");
}
void finalIntegrate(Parameter *param, Atom *atom) {
DEBUG_MESSAGE("finalIntegrate start\n");
for(int ci = 0; ci < atom->Nclusters_local; ci++) {
int ci_vec_base = CI_VECTOR_BASE_INDEX(ci);
MD_FLOAT *ci_v = &atom->cl_v[ci_vec_base];
MD_FLOAT *ci_f = &atom->cl_f[ci_vec_base];
for(int cii = 0; cii < atom->iclusters[ci].natoms; cii++) {
ci_v[CL_X_OFFSET + cii] += param->dtforce * ci_f[CL_X_OFFSET + cii];
ci_v[CL_Y_OFFSET + cii] += param->dtforce * ci_f[CL_Y_OFFSET + cii];
ci_v[CL_Z_OFFSET + cii] += param->dtforce * ci_f[CL_Z_OFFSET + cii];
}
}
DEBUG_MESSAGE("finalIntegrate end\n");
}
void printAtomState(Atom *atom) {
printf("Atom counts: Natoms=%d Nlocal=%d Nghost=%d Nmax=%d\n",
atom->Natoms, atom->Nlocal, atom->Nghost, atom->Nmax);
@ -244,6 +214,11 @@ int main(int argc, char** argv) {
#if defined(MEM_TRACER) || defined(INDEX_TRACER)
traceAddresses(&param, &atom, &neighbor, n + 1);
#endif
#ifdef CUDA_TARGET
copyDataToCUDADevice(&atom);
#endif
if(param.force_field == FF_EAM) {
timer[FORCE] = computeForceEam(&eam, &param, &atom, &neighbor, &stats);
} else {
@ -271,7 +246,16 @@ int main(int argc, char** argv) {
updatePbc(&atom, &param, 0);
} else {
#ifdef CUDA_TARGET
copyDataFromCUDADevice(&atom);
#endif
timer[NEIGH] += reneighbour(&param, &atom, &neighbor);
#ifdef CUDA_TARGET
copyDataToCUDADevice(&atom);
isReneighboured = 1;
#endif
}
#if defined(MEM_TRACER) || defined(INDEX_TRACER)
@ -303,6 +287,10 @@ int main(int argc, char** argv) {
}
}
#ifdef CUDA_TARGET
copyDataFromCUDADevice(&atom);
#endif
timer[TOTAL] = getTimeStamp() - timer[TOTAL];
updateSingleAtoms(&atom);
computeThermo(-1, &param, &atom);
@ -311,6 +299,10 @@ int main(int argc, char** argv) {
xtc_end();
}
#ifdef CUDA_TARGET
cudaDeviceFree();
#endif
printf(HLINE);
printf("System: %d atoms %d ghost atoms, Steps: %d\n", atom.Natoms, atom.Nghost, param.ntimes);
printf("TOTAL %.2fs FORCE %.2fs NEIGH %.2fs REST %.2fs\n",

2
gromacs/pbc.c
View File

@ -29,7 +29,7 @@ void initPbc(Atom* atom) {
/* update coordinates of ghost atoms */
/* uses mapping created in setupPbc */
void updatePbc(Atom *atom, Parameter *param, int firstUpdate) {
void cpuUpdatePbc(Atom *atom, Parameter *param, int firstUpdate) {
DEBUG_MESSAGE("updatePbc start\n");
int jfac = MAX(1, CLUSTER_N / CLUSTER_M);
int ncj = atom->Nclusters_local / jfac;

29
lammps/device_spec.c Normal file
View File

@ -0,0 +1,29 @@
/*
* Copyright (C) 2022 NHR@FAU, University Erlangen-Nuremberg.
* All rights reserved. This file is part of MD-Bench.
* Use of this source code is governed by a LGPL-3.0
* license that can be found in the LICENSE file.
*/
#include <device.h>
#ifdef CUDA_TARGET
void initDevice(Atom *atom, Neighbor *neighbor) {
DeviceAtom *d_atom = &(atom->d_atom);
DeviceNeighbor *d_neighbor = &(neighbor->d_neighbor);
d_atom->epsilon = (MD_FLOAT *) allocateGPU(sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
d_atom->sigma6 = (MD_FLOAT *) allocateGPU(sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
d_atom->cutforcesq = (MD_FLOAT *) allocateGPU(sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
d_neighbor->neighbors = (int *) allocateGPU(sizeof(int) * atom->Nmax * neighbor->maxneighs);
d_neighbor->numneigh = (int *) allocateGPU(sizeof(int) * atom->Nmax);
memcpyToGPU(d_atom->x, atom->x, sizeof(MD_FLOAT) * atom->Nmax * 3);
memcpyToGPU(d_atom->vx, atom->vx, sizeof(MD_FLOAT) * atom->Nmax * 3);
memcpyToGPU(d_atom->sigma6, atom->sigma6, sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
memcpyToGPU(d_atom->epsilon, atom->epsilon, sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
memcpyToGPU(d_atom->cutforcesq, atom->cutforcesq, sizeof(MD_FLOAT) * atom->ntypes * atom->ntypes);
memcpyToGPU(d_atom->type, atom->type, sizeof(int) * atom->Nmax);
}
#endif