--- /dev/null
- #if CUDA_VERSION >= 5500
+/*
+ * This file is part of the GROMACS molecular simulation package.
+ *
+ * Copyright (c) 2012,2013,2014, by the GROMACS development team, led by
+ * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
+ * and including many others, as listed in the AUTHORS file in the
+ * top-level source directory and at http://www.gromacs.org.
+ *
+ * GROMACS is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public License
+ * as published by the Free Software Foundation; either version 2.1
+ * of the License, or (at your option) any later version.
+ *
+ * GROMACS is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with GROMACS; if not, see
+ * http://www.gnu.org/licenses, or write to the Free Software Foundation,
+ * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ *
+ * If you want to redistribute modifications to GROMACS, please
+ * consider that scientific software is very special. Version
+ * control is crucial - bugs must be traceable. We will be happy to
+ * consider code for inclusion in the official distribution, but
+ * derived work must not be called official GROMACS. Details are found
+ * in the README & COPYING files - if they are missing, get the
+ * official version at http://www.gromacs.org.
+ *
+ * To help us fund GROMACS development, we humbly ask that you cite
+ * the research papers on the package. Check out http://www.gromacs.org.
+ */
+#ifdef HAVE_CONFIG_H
+#include <config.h>
+#endif
+
+#include <assert.h>
+#include <stdarg.h>
+#include <stdlib.h>
+#include <stdio.h>
+
+#include <cuda.h>
+
+#include "gmx_fatal.h"
+#include "gromacs/utility/smalloc.h"
+#include "tables.h"
+#include "typedefs.h"
+#include "types/enums.h"
+#include "types/nb_verlet.h"
+#include "types/interaction_const.h"
+#include "types/force_flags.h"
+#include "../nbnxn_consts.h"
+#include "gmx_detect_hardware.h"
+
+#include "nbnxn_cuda_types.h"
+#include "../../gmxlib/cuda_tools/cudautils.cuh"
+#include "nbnxn_cuda_data_mgmt.h"
+#include "pmalloc_cuda.h"
+#include "gpu_utils.h"
+
+#include "gromacs/utility/common.h"
+
+static bool bUseCudaEventBlockingSync = false; /* makes the CPU thread block */
+
+/* This is a heuristically determined parameter for the Fermi architecture for
+ * the minimum size of ci lists by multiplying this constant with the # of
+ * multiprocessors on the current device.
+ */
+static unsigned int gpu_min_ci_balanced_factor = 40;
+
+/* Functions from nbnxn_cuda.cu */
+extern void nbnxn_cuda_set_cacheconfig(cuda_dev_info_t *devinfo);
+extern const struct texture<float, 1, cudaReadModeElementType> &nbnxn_cuda_get_nbfp_texref();
+extern const struct texture<float, 1, cudaReadModeElementType> &nbnxn_cuda_get_nbfp_comb_texref();
+extern const struct texture<float, 1, cudaReadModeElementType> &nbnxn_cuda_get_coulomb_tab_texref();
+
+/* We should actually be using md_print_warn in md_logging.c,
+ * but we can't include mpi.h in CUDA code.
+ */
+static void md_print_warn(FILE *fplog,
+ const char *fmt, ...)
+{
+ va_list ap;
+
+ if (fplog != NULL)
+ {
+ /* We should only print to stderr on the master node,
+ * in most cases fplog is only set on the master node, so this works.
+ */
+ va_start(ap, fmt);
+ fprintf(stderr, "\n");
+ vfprintf(stderr, fmt, ap);
+ fprintf(stderr, "\n");
+ va_end(ap);
+
+ va_start(ap, fmt);
+ fprintf(fplog, "\n");
+ vfprintf(fplog, fmt, ap);
+ fprintf(fplog, "\n");
+ va_end(ap);
+ }
+}
+
+
+/* Fw. decl. */
+static void nbnxn_cuda_clear_e_fshift(nbnxn_cuda_ptr_t cu_nb);
+
+
+/*! Tabulates the Ewald Coulomb force and initializes the size/scale
+ and the table GPU array. If called with an already allocated table,
+ it just re-uploads the table.
+ */
+static void init_ewald_coulomb_force_table(cu_nbparam_t *nbp,
+ const cuda_dev_info_t *dev_info)
+{
+ float *ftmp, *coul_tab;
+ int tabsize;
+ double tabscale;
+ cudaError_t stat;
+
+ tabsize = GPU_EWALD_COULOMB_FORCE_TABLE_SIZE;
+ /* Subtract 2 iso 1 to avoid access out of range due to rounding */
+ tabscale = (tabsize - 2) / sqrt(nbp->rcoulomb_sq);
+
+ pmalloc((void**)&ftmp, tabsize*sizeof(*ftmp));
+
+ table_spline3_fill_ewald_lr(ftmp, NULL, NULL, tabsize,
+ 1/tabscale, nbp->ewald_beta, v_q_ewald_lr);
+
+ /* If the table pointer == NULL the table is generated the first time =>
+ the array pointer will be saved to nbparam and the texture is bound.
+ */
+ coul_tab = nbp->coulomb_tab;
+ if (coul_tab == NULL)
+ {
+ stat = cudaMalloc((void **)&coul_tab, tabsize*sizeof(*coul_tab));
+ CU_RET_ERR(stat, "cudaMalloc failed on coul_tab");
+
+ nbp->coulomb_tab = coul_tab;
+
+#ifdef TEXOBJ_SUPPORTED
+ /* Only device CC >= 3.0 (Kepler and later) support texture objects */
+ if (dev_info->prop.major >= 3)
+ {
+ cudaResourceDesc rd;
+ memset(&rd, 0, sizeof(rd));
+ rd.resType = cudaResourceTypeLinear;
+ rd.res.linear.devPtr = nbp->coulomb_tab;
+ rd.res.linear.desc.f = cudaChannelFormatKindFloat;
+ rd.res.linear.desc.x = 32;
+ rd.res.linear.sizeInBytes = tabsize*sizeof(*coul_tab);
+
+ cudaTextureDesc td;
+ memset(&td, 0, sizeof(td));
+ td.readMode = cudaReadModeElementType;
+ stat = cudaCreateTextureObject(&nbp->coulomb_tab_texobj, &rd, &td, NULL);
+ CU_RET_ERR(stat, "cudaCreateTextureObject on coulomb_tab_texobj failed");
+ }
+ else
+#endif
+ {
+ GMX_UNUSED_VALUE(dev_info);
+ cudaChannelFormatDesc cd = cudaCreateChannelDesc<float>();
+ stat = cudaBindTexture(NULL, &nbnxn_cuda_get_coulomb_tab_texref(),
+ coul_tab, &cd, tabsize*sizeof(*coul_tab));
+ CU_RET_ERR(stat, "cudaBindTexture on coulomb_tab_texref failed");
+ }
+ }
+
+ cu_copy_H2D(coul_tab, ftmp, tabsize*sizeof(*coul_tab));
+
+ nbp->coulomb_tab_size = tabsize;
+ nbp->coulomb_tab_scale = tabscale;
+
+ pfree(ftmp);
+}
+
+
+/*! Initializes the atomdata structure first time, it only gets filled at
+ pair-search. */
+static void init_atomdata_first(cu_atomdata_t *ad, int ntypes)
+{
+ cudaError_t stat;
+
+ ad->ntypes = ntypes;
+ stat = cudaMalloc((void**)&ad->shift_vec, SHIFTS*sizeof(*ad->shift_vec));
+ CU_RET_ERR(stat, "cudaMalloc failed on ad->shift_vec");
+ ad->bShiftVecUploaded = false;
+
+ stat = cudaMalloc((void**)&ad->fshift, SHIFTS*sizeof(*ad->fshift));
+ CU_RET_ERR(stat, "cudaMalloc failed on ad->fshift");
+
+ stat = cudaMalloc((void**)&ad->e_lj, sizeof(*ad->e_lj));
+ CU_RET_ERR(stat, "cudaMalloc failed on ad->e_lj");
+ stat = cudaMalloc((void**)&ad->e_el, sizeof(*ad->e_el));
+ CU_RET_ERR(stat, "cudaMalloc failed on ad->e_el");
+
+ /* initialize to NULL poiters to data that is not allocated here and will
+ need reallocation in nbnxn_cuda_init_atomdata */
+ ad->xq = NULL;
+ ad->f = NULL;
+
+ /* size -1 indicates that the respective array hasn't been initialized yet */
+ ad->natoms = -1;
+ ad->nalloc = -1;
+}
+
+/*! Selects the Ewald kernel type, analytical on SM 3.0 and later, tabulated on
+ earlier GPUs, single or twin cut-off. */
+static int pick_ewald_kernel_type(bool bTwinCut,
+ const cuda_dev_info_t *dev_info)
+{
+ bool bUseAnalyticalEwald, bForceAnalyticalEwald, bForceTabulatedEwald;
+ int kernel_type;
+
+ /* Benchmarking/development environment variables to force the use of
+ analytical or tabulated Ewald kernel. */
+ bForceAnalyticalEwald = (getenv("GMX_CUDA_NB_ANA_EWALD") != NULL);
+ bForceTabulatedEwald = (getenv("GMX_CUDA_NB_TAB_EWALD") != NULL);
+
+ if (bForceAnalyticalEwald && bForceTabulatedEwald)
+ {
+ gmx_incons("Both analytical and tabulated Ewald CUDA non-bonded kernels "
+ "requested through environment variables.");
+ }
+
+ /* By default, on SM 3.0 and later use analytical Ewald, on earlier tabulated. */
+ if ((dev_info->prop.major >= 3 || bForceAnalyticalEwald) && !bForceTabulatedEwald)
+ {
+ bUseAnalyticalEwald = true;
+
+ if (debug)
+ {
+ fprintf(debug, "Using analytical Ewald CUDA kernels\n");
+ }
+ }
+ else
+ {
+ bUseAnalyticalEwald = false;
+
+ if (debug)
+ {
+ fprintf(debug, "Using tabulated Ewald CUDA kernels\n");
+ }
+ }
+
+ /* Use twin cut-off kernels if requested by bTwinCut or the env. var.
+ forces it (use it for debugging/benchmarking only). */
+ if (!bTwinCut && (getenv("GMX_CUDA_NB_EWALD_TWINCUT") == NULL))
+ {
+ kernel_type = bUseAnalyticalEwald ? eelCuEWALD_ANA : eelCuEWALD_TAB;
+ }
+ else
+ {
+ kernel_type = bUseAnalyticalEwald ? eelCuEWALD_ANA_TWIN : eelCuEWALD_TAB_TWIN;
+ }
+
+ return kernel_type;
+}
+
+/*! Copies all parameters related to the cut-off from ic to nbp */
+static void set_cutoff_parameters(cu_nbparam_t *nbp,
+ const interaction_const_t *ic)
+{
+ nbp->ewald_beta = ic->ewaldcoeff_q;
+ nbp->sh_ewald = ic->sh_ewald;
+ nbp->epsfac = ic->epsfac;
+ nbp->two_k_rf = 2.0 * ic->k_rf;
+ nbp->c_rf = ic->c_rf;
+ nbp->rvdw_sq = ic->rvdw * ic->rvdw;
+ nbp->rcoulomb_sq = ic->rcoulomb * ic->rcoulomb;
+ nbp->rlist_sq = ic->rlist * ic->rlist;
+
+ nbp->sh_lj_ewald = ic->sh_lj_ewald;
+ nbp->ewaldcoeff_lj = ic->ewaldcoeff_lj;
+
+ nbp->rvdw_switch = ic->rvdw_switch;
+ nbp->dispersion_shift = ic->dispersion_shift;
+ nbp->repulsion_shift = ic->repulsion_shift;
+ nbp->vdw_switch = ic->vdw_switch;
+}
+
+/*! Initializes the nonbonded parameter data structure. */
+static void init_nbparam(cu_nbparam_t *nbp,
+ const interaction_const_t *ic,
+ const nbnxn_atomdata_t *nbat,
+ const cuda_dev_info_t *dev_info)
+{
+ cudaError_t stat;
+ int ntypes, nnbfp, nnbfp_comb;
+
+ ntypes = nbat->ntype;
+
+ set_cutoff_parameters(nbp, ic);
+
+ if (ic->vdwtype == evdwCUT)
+ {
+ switch (ic->vdw_modifier)
+ {
+ case eintmodNONE:
+ case eintmodPOTSHIFT:
+ nbp->vdwtype = evdwCuCUT;
+ break;
+ case eintmodFORCESWITCH:
+ nbp->vdwtype = evdwCuFSWITCH;
+ break;
+ case eintmodPOTSWITCH:
+ nbp->vdwtype = evdwCuPSWITCH;
+ break;
+ default:
+ gmx_incons("The requested VdW interaction modifier is not implemented in the CUDA GPU accelerated kernels!");
+ break;
+ }
+ }
+ else if (ic->vdwtype == evdwPME)
+ {
+ if (ic->ljpme_comb_rule == ljcrGEOM)
+ {
+ assert(nbat->comb_rule == ljcrGEOM);
+ nbp->vdwtype = evdwCuEWALDGEOM;
+ }
+ else
+ {
+ assert(nbat->comb_rule == ljcrLB);
+ nbp->vdwtype = evdwCuEWALDLB;
+ }
+ }
+ else
+ {
+ gmx_incons("The requested VdW type is not implemented in the CUDA GPU accelerated kernels!");
+ }
+
+ if (ic->eeltype == eelCUT)
+ {
+ nbp->eeltype = eelCuCUT;
+ }
+ else if (EEL_RF(ic->eeltype))
+ {
+ nbp->eeltype = eelCuRF;
+ }
+ else if ((EEL_PME(ic->eeltype) || ic->eeltype == eelEWALD))
+ {
+ /* Initially rcoulomb == rvdw, so it's surely not twin cut-off. */
+ nbp->eeltype = pick_ewald_kernel_type(false, dev_info);
+ }
+ else
+ {
+ /* Shouldn't happen, as this is checked when choosing Verlet-scheme */
+ gmx_incons("The requested electrostatics type is not implemented in the CUDA GPU accelerated kernels!");
+ }
+
+ /* generate table for PME */
+ nbp->coulomb_tab = NULL;
+ if (nbp->eeltype == eelCuEWALD_TAB || nbp->eeltype == eelCuEWALD_TAB_TWIN)
+ {
+ init_ewald_coulomb_force_table(nbp, dev_info);
+ }
+
+ nnbfp = 2*ntypes*ntypes;
+ nnbfp_comb = 2*ntypes;
+
+ stat = cudaMalloc((void **)&nbp->nbfp, nnbfp*sizeof(*nbp->nbfp));
+ CU_RET_ERR(stat, "cudaMalloc failed on nbp->nbfp");
+ cu_copy_H2D(nbp->nbfp, nbat->nbfp, nnbfp*sizeof(*nbp->nbfp));
+
+
+ if (ic->vdwtype == evdwPME)
+ {
+ stat = cudaMalloc((void **)&nbp->nbfp_comb, nnbfp_comb*sizeof(*nbp->nbfp_comb));
+ CU_RET_ERR(stat, "cudaMalloc failed on nbp->nbfp_comb");
+ cu_copy_H2D(nbp->nbfp_comb, nbat->nbfp_comb, nnbfp_comb*sizeof(*nbp->nbfp_comb));
+ }
+
+#ifdef TEXOBJ_SUPPORTED
+ /* Only device CC >= 3.0 (Kepler and later) support texture objects */
+ if (dev_info->prop.major >= 3)
+ {
+ cudaResourceDesc rd;
+ cudaTextureDesc td;
+
+ memset(&rd, 0, sizeof(rd));
+ rd.resType = cudaResourceTypeLinear;
+ rd.res.linear.devPtr = nbp->nbfp;
+ rd.res.linear.desc.f = cudaChannelFormatKindFloat;
+ rd.res.linear.desc.x = 32;
+ rd.res.linear.sizeInBytes = nnbfp*sizeof(*nbp->nbfp);
+
+ memset(&td, 0, sizeof(td));
+ td.readMode = cudaReadModeElementType;
+ stat = cudaCreateTextureObject(&nbp->nbfp_texobj, &rd, &td, NULL);
+ CU_RET_ERR(stat, "cudaCreateTextureObject on nbfp_texobj failed");
+
+ if (ic->vdwtype == evdwPME)
+ {
+ memset(&rd, 0, sizeof(rd));
+ rd.resType = cudaResourceTypeLinear;
+ rd.res.linear.devPtr = nbp->nbfp_comb;
+ rd.res.linear.desc.f = cudaChannelFormatKindFloat;
+ rd.res.linear.desc.x = 32;
+ rd.res.linear.sizeInBytes = nnbfp_comb*sizeof(*nbp->nbfp_comb);
+
+ memset(&td, 0, sizeof(td));
+ td.readMode = cudaReadModeElementType;
+ stat = cudaCreateTextureObject(&nbp->nbfp_comb_texobj, &rd, &td, NULL);
+ CU_RET_ERR(stat, "cudaCreateTextureObject on nbfp_comb_texobj failed");
+ }
+ }
+ else
+#endif
+ {
+ cudaChannelFormatDesc cd = cudaCreateChannelDesc<float>();
+ stat = cudaBindTexture(NULL, &nbnxn_cuda_get_nbfp_texref(),
+ nbp->nbfp, &cd, nnbfp*sizeof(*nbp->nbfp));
+ CU_RET_ERR(stat, "cudaBindTexture on nbfp_texref failed");
+
+ if (ic->vdwtype == evdwPME)
+ {
+ stat = cudaBindTexture(NULL, &nbnxn_cuda_get_nbfp_comb_texref(),
+ nbp->nbfp_comb, &cd, nnbfp_comb*sizeof(*nbp->nbfp_comb));
+ CU_RET_ERR(stat, "cudaBindTexture on nbfp_comb_texref failed");
+ }
+ }
+}
+
+/*! Re-generate the GPU Ewald force table, resets rlist, and update the
+ * electrostatic type switching to twin cut-off (or back) if needed. */
+void nbnxn_cuda_pme_loadbal_update_param(nbnxn_cuda_ptr_t cu_nb,
+ const interaction_const_t *ic)
+{
+ cu_nbparam_t *nbp = cu_nb->nbparam;
+
+ set_cutoff_parameters(nbp, ic);
+
+ nbp->eeltype = pick_ewald_kernel_type(ic->rcoulomb != ic->rvdw,
+ cu_nb->dev_info);
+
+ init_ewald_coulomb_force_table(cu_nb->nbparam, cu_nb->dev_info);
+}
+
+/*! Initializes the pair list data structure. */
+static void init_plist(cu_plist_t *pl)
+{
+ /* initialize to NULL pointers to data that is not allocated here and will
+ need reallocation in nbnxn_cuda_init_pairlist */
+ pl->sci = NULL;
+ pl->cj4 = NULL;
+ pl->excl = NULL;
+
+ /* size -1 indicates that the respective array hasn't been initialized yet */
+ pl->na_c = -1;
+ pl->nsci = -1;
+ pl->sci_nalloc = -1;
+ pl->ncj4 = -1;
+ pl->cj4_nalloc = -1;
+ pl->nexcl = -1;
+ pl->excl_nalloc = -1;
+ pl->bDoPrune = false;
+}
+
+/*! Initializes the timer data structure. */
+static void init_timers(cu_timers_t *t, bool bUseTwoStreams)
+{
+ cudaError_t stat;
+ int eventflags = ( bUseCudaEventBlockingSync ? cudaEventBlockingSync : cudaEventDefault );
+
+ stat = cudaEventCreateWithFlags(&(t->start_atdat), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on start_atdat failed");
+ stat = cudaEventCreateWithFlags(&(t->stop_atdat), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on stop_atdat failed");
+
+ /* The non-local counters/stream (second in the array) are needed only with DD. */
+ for (int i = 0; i <= (bUseTwoStreams ? 1 : 0); i++)
+ {
+ stat = cudaEventCreateWithFlags(&(t->start_nb_k[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on start_nb_k failed");
+ stat = cudaEventCreateWithFlags(&(t->stop_nb_k[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on stop_nb_k failed");
+
+
+ stat = cudaEventCreateWithFlags(&(t->start_pl_h2d[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on start_pl_h2d failed");
+ stat = cudaEventCreateWithFlags(&(t->stop_pl_h2d[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on stop_pl_h2d failed");
+
+ stat = cudaEventCreateWithFlags(&(t->start_nb_h2d[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on start_nb_h2d failed");
+ stat = cudaEventCreateWithFlags(&(t->stop_nb_h2d[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on stop_nb_h2d failed");
+
+ stat = cudaEventCreateWithFlags(&(t->start_nb_d2h[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on start_nb_d2h failed");
+ stat = cudaEventCreateWithFlags(&(t->stop_nb_d2h[i]), eventflags);
+ CU_RET_ERR(stat, "cudaEventCreate on stop_nb_d2h failed");
+ }
+}
+
+/*! Initializes the timings data structure. */
+static void init_timings(wallclock_gpu_t *t)
+{
+ int i, j;
+
+ t->nb_h2d_t = 0.0;
+ t->nb_d2h_t = 0.0;
+ t->nb_c = 0;
+ t->pl_h2d_t = 0.0;
+ t->pl_h2d_c = 0;
+ for (i = 0; i < 2; i++)
+ {
+ for (j = 0; j < 2; j++)
+ {
+ t->ktime[i][j].t = 0.0;
+ t->ktime[i][j].c = 0;
+ }
+ }
+}
+
+void nbnxn_cuda_init(FILE *fplog,
+ nbnxn_cuda_ptr_t *p_cu_nb,
+ const gmx_gpu_info_t *gpu_info,
+ const gmx_gpu_opt_t *gpu_opt,
+ int my_gpu_index,
+ gmx_bool bLocalAndNonlocal)
+{
+ cudaError_t stat;
+ nbnxn_cuda_ptr_t nb;
+ char sbuf[STRLEN];
+ bool bStreamSync, bNoStreamSync, bTMPIAtomics, bX86, bOldDriver;
+ int cuda_drv_ver;
+
+ assert(gpu_info);
+
+ if (p_cu_nb == NULL)
+ {
+ return;
+ }
+
+ snew(nb, 1);
+ snew(nb->atdat, 1);
+ snew(nb->nbparam, 1);
+ snew(nb->plist[eintLocal], 1);
+ if (bLocalAndNonlocal)
+ {
+ snew(nb->plist[eintNonlocal], 1);
+ }
+
+ nb->bUseTwoStreams = bLocalAndNonlocal;
+
+ snew(nb->timers, 1);
+ snew(nb->timings, 1);
+
+ /* init nbst */
+ pmalloc((void**)&nb->nbst.e_lj, sizeof(*nb->nbst.e_lj));
+ pmalloc((void**)&nb->nbst.e_el, sizeof(*nb->nbst.e_el));
+ pmalloc((void**)&nb->nbst.fshift, SHIFTS * sizeof(*nb->nbst.fshift));
+
+ init_plist(nb->plist[eintLocal]);
+
+ /* set device info, just point it to the right GPU among the detected ones */
+ nb->dev_info = &gpu_info->cuda_dev[get_gpu_device_id(gpu_info, gpu_opt, my_gpu_index)];
+
+ /* local/non-local GPU streams */
+ stat = cudaStreamCreate(&nb->stream[eintLocal]);
+ CU_RET_ERR(stat, "cudaStreamCreate on stream[eintLocal] failed");
+ if (nb->bUseTwoStreams)
+ {
+ init_plist(nb->plist[eintNonlocal]);
+
+ /* CUDA stream priority available in the CUDA RT 5.5 API.
+ * Note that the device we're running on does not have to support
+ * priorities, because we are querying the priority range which in this
+ * case will be a single value.
+ */
++#if CUDA_VERSION >= 5050
+ {
+ int highest_priority;
+ stat = cudaDeviceGetStreamPriorityRange(NULL, &highest_priority);
+ CU_RET_ERR(stat, "cudaDeviceGetStreamPriorityRange failed");
+
+ stat = cudaStreamCreateWithPriority(&nb->stream[eintNonlocal],
+ cudaStreamDefault,
+ highest_priority);
+ CU_RET_ERR(stat, "cudaStreamCreateWithPriority on stream[eintNonlocal] failed");
+ }
+#else
+ stat = cudaStreamCreate(&nb->stream[eintNonlocal]);
+ CU_RET_ERR(stat, "cudaStreamCreate on stream[eintNonlocal] failed");
+#endif
+ }
+
+ /* init events for sychronization (timing disabled for performance reasons!) */
+ stat = cudaEventCreateWithFlags(&nb->nonlocal_done, cudaEventDisableTiming);
+ CU_RET_ERR(stat, "cudaEventCreate on nonlocal_done failed");
+ stat = cudaEventCreateWithFlags(&nb->misc_ops_done, cudaEventDisableTiming);
+ CU_RET_ERR(stat, "cudaEventCreate on misc_ops_one failed");
+
+ /* On GPUs with ECC enabled, cudaStreamSynchronize shows a large overhead
+ * (which increases with shorter time/step) caused by a known CUDA driver bug.
+ * To work around the issue we'll use an (admittedly fragile) memory polling
+ * waiting to preserve performance. This requires support for atomic
+ * operations and only works on x86/x86_64.
+ * With polling wait event-timing also needs to be disabled.
+ *
+ * The overhead is greatly reduced in API v5.0 drivers and the improvement
+ * is independent of runtime version. Hence, with API v5.0 drivers and later
+ * we won't switch to polling.
+ *
+ * NOTE: Unfortunately, this is known to fail when GPUs are shared by (t)MPI,
+ * ranks so we will also disable it in that case.
+ */
+
+ bStreamSync = getenv("GMX_CUDA_STREAMSYNC") != NULL;
+ bNoStreamSync = getenv("GMX_NO_CUDA_STREAMSYNC") != NULL;
+
+#ifdef TMPI_ATOMICS
+ bTMPIAtomics = true;
+#else
+ bTMPIAtomics = false;
+#endif
+
+#ifdef GMX_TARGET_X86
+ bX86 = true;
+#else
+ bX86 = false;
+#endif
+
+ if (bStreamSync && bNoStreamSync)
+ {
+ gmx_fatal(FARGS, "Conflicting environment variables: both GMX_CUDA_STREAMSYNC and GMX_NO_CUDA_STREAMSYNC defined");
+ }
+
+ stat = cudaDriverGetVersion(&cuda_drv_ver);
+ CU_RET_ERR(stat, "cudaDriverGetVersion failed");
+
+ bOldDriver = (cuda_drv_ver < 5000);
+
+ if ((nb->dev_info->prop.ECCEnabled == 1) && bOldDriver)
+ {
+ /* Polling wait should be used instead of cudaStreamSynchronize only if:
+ * - ECC is ON & driver is old (checked above),
+ * - we're on x86/x86_64,
+ * - atomics are available, and
+ * - GPUs are not being shared.
+ */
+ bool bShouldUsePollSync = (bX86 && bTMPIAtomics &&
+ (gmx_count_gpu_dev_shared(gpu_opt) < 1));
+
+ if (bStreamSync)
+ {
+ nb->bUseStreamSync = true;
+
+ /* only warn if polling should be used */
+ if (bShouldUsePollSync)
+ {
+ md_print_warn(fplog,
+ "NOTE: Using a GPU with ECC enabled and CUDA driver API version <5.0, but\n"
+ " cudaStreamSynchronize waiting is forced by the GMX_CUDA_STREAMSYNC env. var.\n");
+ }
+ }
+ else
+ {
+ nb->bUseStreamSync = !bShouldUsePollSync;
+
+ if (bShouldUsePollSync)
+ {
+ md_print_warn(fplog,
+ "NOTE: Using a GPU with ECC enabled and CUDA driver API version <5.0, known to\n"
+ " cause performance loss. Switching to the alternative polling GPU wait.\n"
+ " If you encounter issues, switch back to standard GPU waiting by setting\n"
+ " the GMX_CUDA_STREAMSYNC environment variable.\n");
+ }
+ else
+ {
+ /* Tell the user that the ECC+old driver combination can be bad */
+ sprintf(sbuf,
+ "NOTE: Using a GPU with ECC enabled and CUDA driver API version <5.0.\n"
+ " A known bug in this driver version can cause performance loss.\n"
+ " However, the polling wait workaround can not be used because\n%s\n"
+ " Consider updating the driver or turning ECC off.",
+ (bX86 && bTMPIAtomics) ?
+ " GPU(s) are being oversubscribed." :
+ " atomic operations are not supported by the platform/CPU+compiler.");
+ md_print_warn(fplog, sbuf);
+ }
+ }
+ }
+ else
+ {
+ if (bNoStreamSync)
+ {
+ nb->bUseStreamSync = false;
+
+ md_print_warn(fplog,
+ "NOTE: Polling wait for GPU synchronization requested by GMX_NO_CUDA_STREAMSYNC\n");
+ }
+ else
+ {
+ /* no/off ECC, cudaStreamSynchronize not turned off by env. var. */
+ nb->bUseStreamSync = true;
+ }
+ }
+
+ /* CUDA timing disabled as event timers don't work:
+ - with multiple streams = domain-decomposition;
+ - with the polling waiting hack (without cudaStreamSynchronize);
+ - when turned off by GMX_DISABLE_CUDA_TIMING.
+ */
+ nb->bDoTime = (!nb->bUseTwoStreams && nb->bUseStreamSync &&
+ (getenv("GMX_DISABLE_CUDA_TIMING") == NULL));
+
+ if (nb->bDoTime)
+ {
+ init_timers(nb->timers, nb->bUseTwoStreams);
+ init_timings(nb->timings);
+ }
+
+ /* set the kernel type for the current GPU */
+ /* pick L1 cache configuration */
+ nbnxn_cuda_set_cacheconfig(nb->dev_info);
+
+ *p_cu_nb = nb;
+
+ if (debug)
+ {
+ fprintf(debug, "Initialized CUDA data structures.\n");
+ }
+}
+
+void nbnxn_cuda_init_const(nbnxn_cuda_ptr_t cu_nb,
+ const interaction_const_t *ic,
+ const nonbonded_verlet_group_t *nbv_group)
+{
+ init_atomdata_first(cu_nb->atdat, nbv_group[0].nbat->ntype);
+ init_nbparam(cu_nb->nbparam, ic, nbv_group[0].nbat, cu_nb->dev_info);
+
+ /* clear energy and shift force outputs */
+ nbnxn_cuda_clear_e_fshift(cu_nb);
+}
+
+void nbnxn_cuda_init_pairlist(nbnxn_cuda_ptr_t cu_nb,
+ const nbnxn_pairlist_t *h_plist,
+ int iloc)
+{
+ char sbuf[STRLEN];
+ cudaError_t stat;
+ bool bDoTime = cu_nb->bDoTime;
+ cudaStream_t stream = cu_nb->stream[iloc];
+ cu_plist_t *d_plist = cu_nb->plist[iloc];
+
+ if (d_plist->na_c < 0)
+ {
+ d_plist->na_c = h_plist->na_ci;
+ }
+ else
+ {
+ if (d_plist->na_c != h_plist->na_ci)
+ {
+ sprintf(sbuf, "In cu_init_plist: the #atoms per cell has changed (from %d to %d)",
+ d_plist->na_c, h_plist->na_ci);
+ gmx_incons(sbuf);
+ }
+ }
+
+ if (bDoTime)
+ {
+ stat = cudaEventRecord(cu_nb->timers->start_pl_h2d[iloc], stream);
+ CU_RET_ERR(stat, "cudaEventRecord failed");
+ }
+
+ cu_realloc_buffered((void **)&d_plist->sci, h_plist->sci, sizeof(*d_plist->sci),
+ &d_plist->nsci, &d_plist->sci_nalloc,
+ h_plist->nsci,
+ stream, true);
+
+ cu_realloc_buffered((void **)&d_plist->cj4, h_plist->cj4, sizeof(*d_plist->cj4),
+ &d_plist->ncj4, &d_plist->cj4_nalloc,
+ h_plist->ncj4,
+ stream, true);
+
+ cu_realloc_buffered((void **)&d_plist->excl, h_plist->excl, sizeof(*d_plist->excl),
+ &d_plist->nexcl, &d_plist->excl_nalloc,
+ h_plist->nexcl,
+ stream, true);
+
+ if (bDoTime)
+ {
+ stat = cudaEventRecord(cu_nb->timers->stop_pl_h2d[iloc], stream);
+ CU_RET_ERR(stat, "cudaEventRecord failed");
+ }
+
+ /* need to prune the pair list during the next step */
+ d_plist->bDoPrune = true;
+}
+
+void nbnxn_cuda_upload_shiftvec(nbnxn_cuda_ptr_t cu_nb,
+ const nbnxn_atomdata_t *nbatom)
+{
+ cu_atomdata_t *adat = cu_nb->atdat;
+ cudaStream_t ls = cu_nb->stream[eintLocal];
+
+ /* only if we have a dynamic box */
+ if (nbatom->bDynamicBox || !adat->bShiftVecUploaded)
+ {
+ cu_copy_H2D_async(adat->shift_vec, nbatom->shift_vec,
+ SHIFTS * sizeof(*adat->shift_vec), ls);
+ adat->bShiftVecUploaded = true;
+ }
+}
+
+/*! Clears the first natoms_clear elements of the GPU nonbonded force output array. */
+static void nbnxn_cuda_clear_f(nbnxn_cuda_ptr_t cu_nb, int natoms_clear)
+{
+ cudaError_t stat;
+ cu_atomdata_t *adat = cu_nb->atdat;
+ cudaStream_t ls = cu_nb->stream[eintLocal];
+
+ stat = cudaMemsetAsync(adat->f, 0, natoms_clear * sizeof(*adat->f), ls);
+ CU_RET_ERR(stat, "cudaMemsetAsync on f falied");
+}
+
+/*! Clears nonbonded shift force output array and energy outputs on the GPU. */
+static void nbnxn_cuda_clear_e_fshift(nbnxn_cuda_ptr_t cu_nb)
+{
+ cudaError_t stat;
+ cu_atomdata_t *adat = cu_nb->atdat;
+ cudaStream_t ls = cu_nb->stream[eintLocal];
+
+ stat = cudaMemsetAsync(adat->fshift, 0, SHIFTS * sizeof(*adat->fshift), ls);
+ CU_RET_ERR(stat, "cudaMemsetAsync on fshift falied");
+ stat = cudaMemsetAsync(adat->e_lj, 0, sizeof(*adat->e_lj), ls);
+ CU_RET_ERR(stat, "cudaMemsetAsync on e_lj falied");
+ stat = cudaMemsetAsync(adat->e_el, 0, sizeof(*adat->e_el), ls);
+ CU_RET_ERR(stat, "cudaMemsetAsync on e_el falied");
+}
+
+void nbnxn_cuda_clear_outputs(nbnxn_cuda_ptr_t cu_nb, int flags)
+{
+ nbnxn_cuda_clear_f(cu_nb, cu_nb->atdat->natoms);
+ /* clear shift force array and energies if the outputs were
+ used in the current step */
+ if (flags & GMX_FORCE_VIRIAL)
+ {
+ nbnxn_cuda_clear_e_fshift(cu_nb);
+ }
+}
+
+void nbnxn_cuda_init_atomdata(nbnxn_cuda_ptr_t cu_nb,
+ const nbnxn_atomdata_t *nbat)
+{
+ cudaError_t stat;
+ int nalloc, natoms;
+ bool realloced;
+ bool bDoTime = cu_nb->bDoTime;
+ cu_timers_t *timers = cu_nb->timers;
+ cu_atomdata_t *d_atdat = cu_nb->atdat;
+ cudaStream_t ls = cu_nb->stream[eintLocal];
+
+ natoms = nbat->natoms;
+ realloced = false;
+
+ if (bDoTime)
+ {
+ /* time async copy */
+ stat = cudaEventRecord(timers->start_atdat, ls);
+ CU_RET_ERR(stat, "cudaEventRecord failed");
+ }
+
+ /* need to reallocate if we have to copy more atoms than the amount of space
+ available and only allocate if we haven't initialized yet, i.e d_atdat->natoms == -1 */
+ if (natoms > d_atdat->nalloc)
+ {
+ nalloc = over_alloc_small(natoms);
+
+ /* free up first if the arrays have already been initialized */
+ if (d_atdat->nalloc != -1)
+ {
+ cu_free_buffered(d_atdat->f, &d_atdat->natoms, &d_atdat->nalloc);
+ cu_free_buffered(d_atdat->xq);
+ cu_free_buffered(d_atdat->atom_types);
+ }
+
+ stat = cudaMalloc((void **)&d_atdat->f, nalloc*sizeof(*d_atdat->f));
+ CU_RET_ERR(stat, "cudaMalloc failed on d_atdat->f");
+ stat = cudaMalloc((void **)&d_atdat->xq, nalloc*sizeof(*d_atdat->xq));
+ CU_RET_ERR(stat, "cudaMalloc failed on d_atdat->xq");
+
+ stat = cudaMalloc((void **)&d_atdat->atom_types, nalloc*sizeof(*d_atdat->atom_types));
+ CU_RET_ERR(stat, "cudaMalloc failed on d_atdat->atom_types");
+
+ d_atdat->nalloc = nalloc;
+ realloced = true;
+ }
+
+ d_atdat->natoms = natoms;
+ d_atdat->natoms_local = nbat->natoms_local;
+
+ /* need to clear GPU f output if realloc happened */
+ if (realloced)
+ {
+ nbnxn_cuda_clear_f(cu_nb, nalloc);
+ }
+
+ cu_copy_H2D_async(d_atdat->atom_types, nbat->type,
+ natoms*sizeof(*d_atdat->atom_types), ls);
+
+ if (bDoTime)
+ {
+ stat = cudaEventRecord(timers->stop_atdat, ls);
+ CU_RET_ERR(stat, "cudaEventRecord failed");
+ }
+}
+
+void nbnxn_cuda_free(nbnxn_cuda_ptr_t cu_nb)
+{
+ cudaError_t stat;
+ cu_atomdata_t *atdat;
+ cu_nbparam_t *nbparam;
+ cu_plist_t *plist, *plist_nl;
+ cu_timers_t *timers;
+
+ if (cu_nb == NULL)
+ {
+ return;
+ }
+
+ atdat = cu_nb->atdat;
+ nbparam = cu_nb->nbparam;
+ plist = cu_nb->plist[eintLocal];
+ plist_nl = cu_nb->plist[eintNonlocal];
+ timers = cu_nb->timers;
+
+ if (nbparam->eeltype == eelCuEWALD_TAB || nbparam->eeltype == eelCuEWALD_TAB_TWIN)
+ {
+
+#ifdef TEXOBJ_SUPPORTED
+ /* Only device CC >= 3.0 (Kepler and later) support texture objects */
+ if (cu_nb->dev_info->prop.major >= 3)
+ {
+ stat = cudaDestroyTextureObject(nbparam->coulomb_tab_texobj);
+ CU_RET_ERR(stat, "cudaDestroyTextureObject on coulomb_tab_texobj failed");
+ }
+ else
+#endif
+ {
+ stat = cudaUnbindTexture(nbnxn_cuda_get_coulomb_tab_texref());
+ CU_RET_ERR(stat, "cudaUnbindTexture on coulomb_tab_texref failed");
+ }
+ cu_free_buffered(nbparam->coulomb_tab, &nbparam->coulomb_tab_size);
+ }
+
+ stat = cudaEventDestroy(cu_nb->nonlocal_done);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->nonlocal_done");
+ stat = cudaEventDestroy(cu_nb->misc_ops_done);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->misc_ops_done");
+
+ if (cu_nb->bDoTime)
+ {
+ stat = cudaEventDestroy(timers->start_atdat);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->start_atdat");
+ stat = cudaEventDestroy(timers->stop_atdat);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->stop_atdat");
+
+ /* The non-local counters/stream (second in the array) are needed only with DD. */
+ for (int i = 0; i <= (cu_nb->bUseTwoStreams ? 1 : 0); i++)
+ {
+ stat = cudaEventDestroy(timers->start_nb_k[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->start_nb_k");
+ stat = cudaEventDestroy(timers->stop_nb_k[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->stop_nb_k");
+
+ stat = cudaEventDestroy(timers->start_pl_h2d[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->start_pl_h2d");
+ stat = cudaEventDestroy(timers->stop_pl_h2d[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->stop_pl_h2d");
+
+ stat = cudaStreamDestroy(cu_nb->stream[i]);
+ CU_RET_ERR(stat, "cudaStreamDestroy failed on stream");
+
+ stat = cudaEventDestroy(timers->start_nb_h2d[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->start_nb_h2d");
+ stat = cudaEventDestroy(timers->stop_nb_h2d[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->stop_nb_h2d");
+
+ stat = cudaEventDestroy(timers->start_nb_d2h[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->start_nb_d2h");
+ stat = cudaEventDestroy(timers->stop_nb_d2h[i]);
+ CU_RET_ERR(stat, "cudaEventDestroy failed on timers->stop_nb_d2h");
+ }
+ }
+
+#ifdef TEXOBJ_SUPPORTED
+ /* Only device CC >= 3.0 (Kepler and later) support texture objects */
+ if (cu_nb->dev_info->prop.major >= 3)
+ {
+ stat = cudaDestroyTextureObject(nbparam->nbfp_texobj);
+ CU_RET_ERR(stat, "cudaDestroyTextureObject on nbfp_texobj failed");
+ }
+ else
+#endif
+ {
+ stat = cudaUnbindTexture(nbnxn_cuda_get_nbfp_texref());
+ CU_RET_ERR(stat, "cudaUnbindTexture on nbfp_texref failed");
+ }
+ cu_free_buffered(nbparam->nbfp);
+
+ if (nbparam->vdwtype == evdwCuEWALDGEOM || nbparam->vdwtype == evdwCuEWALDLB)
+ {
+#ifdef TEXOBJ_SUPPORTED
+ /* Only device CC >= 3.0 (Kepler and later) support texture objects */
+ if (cu_nb->dev_info->prop.major >= 3)
+ {
+ stat = cudaDestroyTextureObject(nbparam->nbfp_comb_texobj);
+ CU_RET_ERR(stat, "cudaDestroyTextureObject on nbfp_comb_texobj failed");
+ }
+ else
+#endif
+ {
+ stat = cudaUnbindTexture(nbnxn_cuda_get_nbfp_comb_texref());
+ CU_RET_ERR(stat, "cudaUnbindTexture on nbfp_comb_texref failed");
+ }
+ cu_free_buffered(nbparam->nbfp_comb);
+ }
+
+ stat = cudaFree(atdat->shift_vec);
+ CU_RET_ERR(stat, "cudaFree failed on atdat->shift_vec");
+ stat = cudaFree(atdat->fshift);
+ CU_RET_ERR(stat, "cudaFree failed on atdat->fshift");
+
+ stat = cudaFree(atdat->e_lj);
+ CU_RET_ERR(stat, "cudaFree failed on atdat->e_lj");
+ stat = cudaFree(atdat->e_el);
+ CU_RET_ERR(stat, "cudaFree failed on atdat->e_el");
+
+ cu_free_buffered(atdat->f, &atdat->natoms, &atdat->nalloc);
+ cu_free_buffered(atdat->xq);
+ cu_free_buffered(atdat->atom_types, &atdat->ntypes);
+
+ cu_free_buffered(plist->sci, &plist->nsci, &plist->sci_nalloc);
+ cu_free_buffered(plist->cj4, &plist->ncj4, &plist->cj4_nalloc);
+ cu_free_buffered(plist->excl, &plist->nexcl, &plist->excl_nalloc);
+ if (cu_nb->bUseTwoStreams)
+ {
+ cu_free_buffered(plist_nl->sci, &plist_nl->nsci, &plist_nl->sci_nalloc);
+ cu_free_buffered(plist_nl->cj4, &plist_nl->ncj4, &plist_nl->cj4_nalloc);
+ cu_free_buffered(plist_nl->excl, &plist_nl->nexcl, &plist->excl_nalloc);
+ }
+
+ sfree(atdat);
+ sfree(nbparam);
+ sfree(plist);
+ if (cu_nb->bUseTwoStreams)
+ {
+ sfree(plist_nl);
+ }
+ sfree(timers);
+ sfree(cu_nb->timings);
+ sfree(cu_nb);
+
+ if (debug)
+ {
+ fprintf(debug, "Cleaned up CUDA data structures.\n");
+ }
+}
+
+void cu_synchstream_atdat(nbnxn_cuda_ptr_t cu_nb, int iloc)
+{
+ cudaError_t stat;
+ cudaStream_t stream = cu_nb->stream[iloc];
+
+ stat = cudaStreamWaitEvent(stream, cu_nb->timers->stop_atdat, 0);
+ CU_RET_ERR(stat, "cudaStreamWaitEvent failed");
+}
+
+wallclock_gpu_t * nbnxn_cuda_get_timings(nbnxn_cuda_ptr_t cu_nb)
+{
+ return (cu_nb != NULL && cu_nb->bDoTime) ? cu_nb->timings : NULL;
+}
+
+void nbnxn_cuda_reset_timings(nbnxn_cuda_ptr_t cu_nb)
+{
+ if (cu_nb->bDoTime)
+ {
+ init_timings(cu_nb->timings);
+ }
+}
+
+int nbnxn_cuda_min_ci_balanced(nbnxn_cuda_ptr_t cu_nb)
+{
+ return cu_nb != NULL ?
+ gpu_min_ci_balanced_factor*cu_nb->dev_info->prop.multiProcessorCount : 0;
+
+}
+
+gmx_bool nbnxn_cuda_is_kernel_ewald_analytical(const nbnxn_cuda_ptr_t cu_nb)
+{
+ return ((cu_nb->nbparam->eeltype == eelCuEWALD_ANA) ||
+ (cu_nb->nbparam->eeltype == eelCuEWALD_ANA_TWIN));
+}
biod.pnpi.spb.ru / alexxy / gromacs.git / commitdiff