/*************************************************************************** lal_table.cpp ------------------- Trung Dac Nguyen (ORNL) Functions for LAMMPS access to table acceleration routines. __________________________________________________________________________ This file is part of the LAMMPS Accelerator Library (LAMMPS_AL) __________________________________________________________________________ begin : email : nguyentd@ornl.gov ***************************************************************************/ #include #include #include #include "lal_table.h" using namespace std; using namespace LAMMPS_AL; static Table TBMF; // --------------------------------------------------------------------------- // Allocate memory on host and device and copy constants to device // --------------------------------------------------------------------------- int table_gpu_init(const int ntypes, double **cutsq, double ***table_coeffs, double **table_data, 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, int tabstyle, int ntables, int tablength) { TBMF.clear(); gpu_mode=TBMF.device->gpu_mode(); double gpu_split=TBMF.device->particle_split(); int first_gpu=TBMF.device->first_device(); int last_gpu=TBMF.device->last_device(); int world_me=TBMF.device->world_me(); int gpu_rank=TBMF.device->gpu_rank(); int procs_per_gpu=TBMF.device->procs_per_gpu(); TBMF.device->init_message(screen,"table",first_gpu,last_gpu); bool message=false; if (TBMF.device->replica_me()==0 && screen) message=true; if (message) { fprintf(screen,"Initializing Device and compiling on process 0..."); fflush(screen); } int init_ok=0; if (world_me==0) init_ok=TBMF.init(ntypes, cutsq, table_coeffs, table_data, special_lj, inum, nall, 300, maxspecial, cell_size, gpu_split, screen, tabstyle, ntables, tablength); TBMF.device->world_barrier(); if (message) fprintf(screen,"Done.\n"); for (int i=0; igpu_barrier(); if (message) fprintf(screen,"Done.\n"); } if (message) fprintf(screen,"\n"); if (init_ok==0) TBMF.estimate_gpu_overhead(); return init_ok; } void table_gpu_clear() { TBMF.clear(); } int ** table_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) { return TBMF.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); } void table_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) { TBMF.compute(ago,inum_full,nall,host_x,host_type,ilist,numj, firstneigh,eflag,vflag,eatom,vatom,host_start,cpu_time,success); } double table_gpu_bytes() { return TBMF.host_memory_usage(); }