Wrong logic was used

[gromacs.git] / src / gromacs / nbnxm / nbnxm_gpu_data_mgmt.cpp

/*
 * This file is part of the GROMACS molecular simulation package.
 *
 * Copyright (c) 2012,2013,2014,2015,2016 by the GROMACS development team.
 * Copyright (c) 2017,2018,2019,2020, 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.
 */
/*! \internal \file
 *  \brief Define common implementation of nbnxm_gpu_data_mgmt.h
 *
 *  \author Anca Hamuraru <anca@streamcomputing.eu>
 *  \author Dimitrios Karkoulis <dimitris.karkoulis@gmail.com>
 *  \author Teemu Virolainen <teemu@streamcomputing.eu>
 *  \author Szilárd Páll <pall.szilard@gmail.com>
 *  \author Artem Zhmurov <zhmurov@gmail.com>
 *
 *  \ingroup module_nbnxm
 */
#include "gmxpre.h"

#include "config.h"

#if GMX_GPU_CUDA
#    include "cuda/nbnxm_cuda_types.h"
#endif

#if GMX_GPU_OPENCL
#    include "opencl/nbnxm_ocl_types.h"
#endif

#include "nbnxm_gpu_data_mgmt.h"

#include "gromacs/nbnxm/gpu_data_mgmt.h"
#include "gromacs/timing/gpu_timing.h"
#include "gromacs/utility/cstringutil.h"

#include "nbnxm_gpu.h"
#include "pairlistsets.h"

namespace Nbnxm
{

void init_ewald_coulomb_force_table(const EwaldCorrectionTables& tables,
                                    NBParamGpu*                  nbp,
                                    const DeviceContext&         deviceContext)
{
    if (!nbp->coulomb_tab)
    {
        destroyParamLookupTable(&nbp->coulomb_tab, nbp->coulomb_tab_texobj);
    }

    nbp->coulomb_tab_scale = tables.scale;
    initParamLookupTable(&nbp->coulomb_tab, &nbp->coulomb_tab_texobj, tables.tableF.data(),
                         tables.tableF.size(), deviceContext);
}

void inline printEnviromnentVariableDeprecationMessage(bool               isEnvironmentVariableSet,
                                                       const std::string& environmentVariableSuffix)
{
    if (isEnvironmentVariableSet)
    {
        fprintf(stderr,
                "Environment variables GMX_CUDA_%s and GMX_OCL_%s are deprecated and will be\n"
                "removed in release 2022, please use GMX_GPU_%s instead.",
                environmentVariableSuffix.c_str(), environmentVariableSuffix.c_str(),
                environmentVariableSuffix.c_str());
    }
}

int nbnxn_gpu_pick_ewald_kernel_type(const interaction_const_t& ic)
{
    bool bTwinCut = (ic.rcoulomb != ic.rvdw);
    int  kernel_type;

    /* Benchmarking/development environment variables to force the use of
       analytical or tabulated Ewald kernel. */

    // Remove these when old environment variables are deprecated
    const bool forceAnalyticalEwaldLegacy = (getenv("GMX_CUDA_NB_ANA_EWALD") != nullptr)
                                            || (getenv("GMX_OCL_NB_ANA_EWALD") != nullptr);
    const bool forceTabulatedEwaldLegacy = (getenv("GMX_CUDA_NB_TAB_EWALD") != nullptr)
                                           || (getenv("GMX_OCL_NB_TAB_EWALD") != nullptr);
    const bool forceTwinCutoffEwaldLegacy = (getenv("GMX_CUDA_NB_EWALD_TWINCUT") != nullptr)
                                            || (getenv("GMX_OCL_NB_EWALD_TWINCUT") != nullptr);

    printEnviromnentVariableDeprecationMessage(forceAnalyticalEwaldLegacy, "NB_ANA_EWALD");
    printEnviromnentVariableDeprecationMessage(forceTabulatedEwaldLegacy, "NB_TAB_EWALD");
    printEnviromnentVariableDeprecationMessage(forceTwinCutoffEwaldLegacy, "NB_EWALD_TWINCUT");

    const bool forceAnalyticalEwald =
            (getenv("GMX_GPU_NB_ANA_EWALD") != nullptr) || forceAnalyticalEwaldLegacy;
    const bool forceTabulatedEwald =
            (getenv("GMX_GPU_NB_TAB_EWALD") != nullptr) || forceTabulatedEwaldLegacy;

    if (forceAnalyticalEwald && forceTabulatedEwald)
    {
        gmx_incons(
                "Both analytical and tabulated Ewald GPU non-bonded kernels "
                "requested through environment variables.");
    }

    /* By default, use analytical Ewald
     * TODO: tabulated does not work in OpenCL, it needs fixing, see init_nbparam() in nbnxn_ocl_data_mgmt.cpp
     *
     */
    bool bUseAnalyticalEwald = true;
    if (forceAnalyticalEwald)
    {
        if (debug)
        {
            fprintf(debug, "Using analytical Ewald GPU kernels\n");
        }
    }
    else if (forceTabulatedEwald)
    {
        bUseAnalyticalEwald = false;

        if (debug)
        {
            fprintf(debug, "Using tabulated Ewald GPU 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_GPU_NB_EWALD_TWINCUT") == nullptr) || forceTwinCutoffEwaldLegacy))
    {
        kernel_type = bUseAnalyticalEwald ? eelTypeEWALD_ANA : eelTypeEWALD_TAB;
    }
    else
    {
        kernel_type = bUseAnalyticalEwald ? eelTypeEWALD_ANA_TWIN : eelTypeEWALD_TAB_TWIN;
    }

    return kernel_type;
}

void set_cutoff_parameters(NBParamGpu* nbp, const interaction_const_t* ic, const PairlistParams& listParams)
{
    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->rlistOuter_sq     = listParams.rlistOuter * listParams.rlistOuter;
    nbp->rlistInner_sq     = listParams.rlistInner * listParams.rlistInner;
    nbp->useDynamicPruning = listParams.useDynamicPruning;

    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;
}

void gpu_pme_loadbal_update_param(const nonbonded_verlet_t* nbv, const interaction_const_t* ic)
{
    if (!nbv || !nbv->useGpu())
    {
        return;
    }
    NbnxmGpu*   nb  = nbv->gpu_nbv;
    NBParamGpu* nbp = nb->nbparam;

    set_cutoff_parameters(nbp, ic, nbv->pairlistSets().params());

    nbp->eeltype = nbnxn_gpu_pick_ewald_kernel_type(*ic);

    GMX_RELEASE_ASSERT(ic->coulombEwaldTables, "Need valid Coulomb Ewald correction tables");
    init_ewald_coulomb_force_table(*ic->coulombEwaldTables, nbp, *nb->deviceContext_);
}

void init_plist(gpu_plist* pl)
{
    /* initialize to nullptr pointers to data that is not allocated here and will
       need reallocation in nbnxn_gpu_init_pairlist */
    pl->sci   = nullptr;
    pl->cj4   = nullptr;
    pl->imask = nullptr;
    pl->excl  = nullptr;

    /* 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->nimask        = -1;
    pl->imask_nalloc  = -1;
    pl->nexcl         = -1;
    pl->excl_nalloc   = -1;
    pl->haveFreshList = false;
}

void init_timings(gmx_wallclock_gpu_nbnxn_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;
        }
    }
    t->pruneTime.c        = 0;
    t->pruneTime.t        = 0.0;
    t->dynamicPruneTime.c = 0;
    t->dynamicPruneTime.t = 0.0;
}

//! This function is documented in the header file
void gpu_init_pairlist(NbnxmGpu* nb, const NbnxnPairlistGpu* h_plist, const InteractionLocality iloc)
{
    char sbuf[STRLEN];
    // Timing accumulation should happen only if there was work to do
    // because getLastRangeTime() gets skipped with empty lists later
    // which leads to the counter not being reset.
    bool                bDoTime      = (nb->bDoTime && !h_plist->sci.empty());
    const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
    gpu_plist*          d_plist      = 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 init_plist: the #atoms per cell has changed (from %d to %d)",
                    d_plist->na_c, h_plist->na_ci);
            gmx_incons(sbuf);
        }
    }

    gpu_timers_t::Interaction& iTimers = nb->timers->interaction[iloc];

    if (bDoTime)
    {
        iTimers.pl_h2d.openTimingRegion(deviceStream);
        iTimers.didPairlistH2D = true;
    }

    // TODO most of this function is same in CUDA and OpenCL, move into the header
    const DeviceContext& deviceContext = *nb->deviceContext_;

    reallocateDeviceBuffer(&d_plist->sci, h_plist->sci.size(), &d_plist->nsci, &d_plist->sci_nalloc,
                           deviceContext);
    copyToDeviceBuffer(&d_plist->sci, h_plist->sci.data(), 0, h_plist->sci.size(), deviceStream,
                       GpuApiCallBehavior::Async, bDoTime ? iTimers.pl_h2d.fetchNextEvent() : nullptr);

    reallocateDeviceBuffer(&d_plist->cj4, h_plist->cj4.size(), &d_plist->ncj4, &d_plist->cj4_nalloc,
                           deviceContext);
    copyToDeviceBuffer(&d_plist->cj4, h_plist->cj4.data(), 0, h_plist->cj4.size(), deviceStream,
                       GpuApiCallBehavior::Async, bDoTime ? iTimers.pl_h2d.fetchNextEvent() : nullptr);

    reallocateDeviceBuffer(&d_plist->imask, h_plist->cj4.size() * c_nbnxnGpuClusterpairSplit,
                           &d_plist->nimask, &d_plist->imask_nalloc, deviceContext);

    reallocateDeviceBuffer(&d_plist->excl, h_plist->excl.size(), &d_plist->nexcl,
                           &d_plist->excl_nalloc, deviceContext);
    copyToDeviceBuffer(&d_plist->excl, h_plist->excl.data(), 0, h_plist->excl.size(), deviceStream,
                       GpuApiCallBehavior::Async, bDoTime ? iTimers.pl_h2d.fetchNextEvent() : nullptr);

    if (bDoTime)
    {
        iTimers.pl_h2d.closeTimingRegion(deviceStream);
    }

    /* need to prune the pair list during the next step */
    d_plist->haveFreshList = true;
}

//! This function is documented in the header file
gmx_wallclock_gpu_nbnxn_t* gpu_get_timings(NbnxmGpu* nb)
{
    return (nb != nullptr && nb->bDoTime) ? nb->timings : nullptr;
}

//! This function is documented in the header file
void gpu_reset_timings(nonbonded_verlet_t* nbv)
{
    if (nbv->gpu_nbv && nbv->gpu_nbv->bDoTime)
    {
        init_timings(nbv->gpu_nbv->timings);
    }
}

bool gpu_is_kernel_ewald_analytical(const NbnxmGpu* nb)
{
    return ((nb->nbparam->eeltype == eelTypeEWALD_ANA) || (nb->nbparam->eeltype == eelTypeEWALD_ANA_TWIN));
}

} // namespace Nbnxm