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git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@12169 f3b2605a-c512-4ea7-a41b-209d697bcdaa

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sjplimp
2014-07-02 20:53:37 +00:00
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commit b5d89cd768
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143
lib/gpu/lal_coul_ext.cpp Normal file
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/***************************************************************************
coul_ext.cpp
-------------------
Trung Dac Nguyen
Functions for LAMMPS access to coul/cut acceleration routines.
__________________________________________________________________________
This file is part of the LAMMPS Accelerator Library (LAMMPS_AL)
__________________________________________________________________________
begin :
email : ndtrung@umich.edu
***************************************************************************/
#include <iostream>
#include <cassert>
#include <math.h>
#include "lal_coul.h"
using namespace std;
using namespace LAMMPS_AL;
static Coul<PRECISION,ACC_PRECISION> COULMF;
// ---------------------------------------------------------------------------
// Allocate memory on host and device and copy constants to device
// ---------------------------------------------------------------------------
int coul_gpu_init(const int ntypes, double **host_scale,
double **cutsq, double *special_coul,
const int inum, const int nall, const int max_nbors,
const int maxspecial, const double cell_size,
int &gpu_mode, FILE *screen, const double qqrd2e) {
COULMF.clear();
gpu_mode=COULMF.device->gpu_mode();
double gpu_split=COULMF.device->particle_split();
int first_gpu=COULMF.device->first_device();
int last_gpu=COULMF.device->last_device();
int world_me=COULMF.device->world_me();
int gpu_rank=COULMF.device->gpu_rank();
int procs_per_gpu=COULMF.device->procs_per_gpu();
COULMF.device->init_message(screen,"coul/cut",first_gpu,last_gpu);
bool message=false;
if (COULMF.device->replica_me()==0 && screen)
message=true;
if (message) {
fprintf(screen,"Initializing GPU and compiling on process 0...");
fflush(screen);
}
int init_ok=0;
if (world_me==0)
init_ok=COULMF.init(ntypes, host_scale, cutsq, special_coul, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen, qqrd2e);
COULMF.device->world_barrier();
if (message)
fprintf(screen,"Done.\n");
for (int i=0; i<procs_per_gpu; i++) {
if (message) {
if (last_gpu-first_gpu==0)
fprintf(screen,"Initializing GPU %d on core %d...",first_gpu,i);
else
fprintf(screen,"Initializing GPUs %d-%d on core %d...",first_gpu,
last_gpu,i);
fflush(screen);
}
if (gpu_rank==i && world_me!=0)
init_ok=COULMF.init(ntypes, host_scale, cutsq, special_coul, inum, nall, 300,
maxspecial, cell_size, gpu_split, screen, qqrd2e);
COULMF.device->gpu_barrier();
if (message)
fprintf(screen,"Done.\n");
}
if (message)
fprintf(screen,"\n");
if (init_ok==0)
COULMF.estimate_gpu_overhead();
return init_ok;
}
// ---------------------------------------------------------------------------
// Copy updated constants to device
// ---------------------------------------------------------------------------
void coul_gpu_reinit(const int ntypes, double **host_scale) {
int world_me=COULMF.device->world_me();
int gpu_rank=COULMF.device->gpu_rank();
int procs_per_gpu=COULMF.device->procs_per_gpu();
if (world_me==0)
COULMF.reinit(ntypes, host_scale);
COULMF.device->world_barrier();
for (int i=0; i<procs_per_gpu; i++) {
if (gpu_rank==i && world_me!=0)
COULMF.reinit(ntypes, host_scale);
COULMF.device->gpu_barrier();
}
}
void coul_gpu_clear() {
COULMF.clear();
}
int** coul_gpu_compute_n(const int ago, const int inum_full,
const int nall, double **host_x, int *host_type,
double *sublo, double *subhi, tagint *tag, int **nspecial,
tagint **special, const bool eflag, const bool vflag,
const bool eatom, const bool vatom, int &host_start,
int **ilist, int **jnum, const double cpu_time,
bool &success, double *host_q, double *boxlo,
double *prd) {
return COULMF.compute(ago, inum_full, nall, host_x, host_type, sublo,
subhi, tag, nspecial, special, eflag, vflag, eatom,
vatom, host_start, ilist, jnum, cpu_time, success,
host_q, boxlo, prd);
}
void coul_gpu_compute(const int ago, const int inum_full, const int nall,
double **host_x, int *host_type, int *ilist, int *numj,
int **firstneigh, const bool eflag, const bool vflag,
const bool eatom, const bool vatom, int &host_start,
const double cpu_time, bool &success, double *host_q,
const int nlocal, double *boxlo, double *prd) {
COULMF.compute(ago,inum_full,nall,host_x,host_type,ilist,numj,firstneigh,eflag,
vflag,eatom,vatom,host_start,cpu_time,success,host_q,
nlocal,boxlo,prd);
}
double coul_gpu_bytes() {
return COULMF.host_memory_usage();
}