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cmmc_msm_gpu.cpp
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cmmc_msm_gpu.cpp
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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 (ORNL), brownw@ornl.gov
			------------------------------------------------------------------------- */

			#include <iostream>
			#include <cassert>
			#include <math.h>

			#include "cmmc_msm_gpu_memory.h"

			using namespace std;

			static CMMM_GPU_Memory<PRECISION,ACC_PRECISION> CMMMMF;

			// ---------------------------------------------------------------------------
			// Allocate memory on host and device and copy constants to device
			// ---------------------------------------------------------------------------
			int cmmm_gpu_init(const int ntypes, double cutsq, int cg_type,
			double host_lj1, double host_lj2, double **host_lj3,
			double host_lj4, double offset, double *special_lj,
			const int inum, const int nall, const int max_nbors,
			const int maxspecial, const double cell_size, int &gpu_mode,
			FILE screen, double *host_cut_ljsq, double host_cut_coulsq,
			double *host_special_coul, const double qqrd2e,
			const int smooth) {
			CMMMMF.clear();
			gpu_mode=CMMMMF.device->gpu_mode();
			double gpu_split=CMMMMF.device->particle_split();
			int first_gpu=CMMMMF.device->first_device();
			int last_gpu=CMMMMF.device->last_device();
			int world_me=CMMMMF.device->world_me();
			int gpu_rank=CMMMMF.device->gpu_rank();
			int procs_per_gpu=CMMMMF.device->procs_per_gpu();

			CMMMMF.device->init_message(screen,"cg/cmm/coul/msm",first_gpu,last_gpu);

			bool message=false;
			if (CMMMMF.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=CMMMMF.init(ntypes, cutsq, cg_type, host_lj1, host_lj2, host_lj3,
			host_lj4, offset, special_lj, inum, nall, 300,
			maxspecial, cell_size, gpu_split, screen, host_cut_ljsq,
			host_cut_coulsq, host_special_coul, qqrd2e,smooth);

			CMMMMF.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=CMMMMF.init(ntypes, cutsq, cg_type, host_lj1, host_lj2, host_lj3,
			host_lj4, offset, special_lj, inum, nall, 300,
			maxspecial, cell_size, gpu_split, screen,
			host_cut_ljsq, host_cut_coulsq, host_special_coul,
			qqrd2e,smooth);

			CMMMMF.device->gpu_barrier();
			if (message)
			fprintf(screen,"Done.\n");
			}
			if (message)
			fprintf(screen,"\n");

			if (init_ok==0)
			CMMMMF.estimate_gpu_overhead();
			return init_ok;
			}

			void cmmm_gpu_clear() {
			CMMMMF.clear();
			}

			int** cmmm_gpu_compute_n(const int ago, const int inum_full,
			const int nall, double *host_x, int host_type,
			double sublo, double subhi, int tag, int *nspecial,
			int **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 CMMMMF.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 cmmm_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) {
			CMMMMF.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 cmmm_gpu_bytes() {
			return CMMMMF.host_memory_usage();
			}

lammps/lib/gpu/cmmc_msm_gpu.cpp945343265e0eefficient_neuronet

cmmc_msm_gpu.cppView Options

lammps/lib/gpu/cmmc_msm_gpu.cpp
945343265e0eefficient_neuronet

cmmc_msm_gpu.cpp
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