src/gromacs/ewald/pme_gpu_program_impl.h

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  35 /*! \internal \file
  36  * \brief
  37  * Declares PmeGpuProgramImpl, which stores PME GPU (compiled) kernel handles.
  38  *
  39  * \author Aleksei Iupinov <a.yupinov@gmail.com>
  40  * \ingroup module_ewald
  41  */
  42 #ifndef GMX_EWALD_PME_PME_GPU_PROGRAM_IMPL_H
  43 #define GMX_EWALD_PME_PME_GPU_PROGRAM_IMPL_H
  44
  45 #include "config.h"
  46
  47 #include "gromacs/gpu_utils/device_context.h"
  48 #include "gromacs/gpu_utils/gputraits.h"
  49 #include "gromacs/utility/classhelpers.h"
  50
  51 class DeviceContext;
  52 struct DeviceInformation;
  53
  54 /*! \internal
  55  * \brief
  56  * PME GPU persistent host program/kernel data, which should be initialized once for the whole execution.
  57  *
  58  * Primary purpose of this is to not recompile GPU kernels for each OpenCL unit test,
  59  * while the relevant GPU context (e.g. cl_context) instance persists.
  60  * In CUDA, this just assigns the kernel function pointers.
  61  * This also implicitly relies on the fact that reasonable share of the kernels are always used.
  62  * If there were more template parameters, even smaller share of all possible kernels would be used.
  63  *
  64  * \todo In future if we would need to react to either user input or
  65  * auto-tuning to compile different kernels, then we might wish to
  66  * revisit the number of kernels we pre-compile, and/or the management
  67  * of their lifetime.
  68  *
  69  * This also doesn't manage cuFFT/clFFT kernels, which depend on the PME grid dimensions.
  70  *
  71  * TODO: pass cl_context to the constructor and not create it inside.
  72  * See also Issue #2522.
  73  */
  74 struct PmeGpuProgramImpl
  75 {
  76     /*! \brief
  77      * This is a handle to the GPU context, which is just a dummy in CUDA,
  78      * but is created/destroyed by this class in OpenCL.
  79      */
  80     const DeviceContext& deviceContext_;
  81
  82     //! Conveniently all the PME kernels use the same single argument type
  83 #if GMX_GPU == GMX_GPU_CUDA
  84     using PmeKernelHandle = void (*)(const struct PmeGpuCudaKernelParams);
  85 #elif GMX_GPU == GMX_GPU_OPENCL
  86     using PmeKernelHandle = cl_kernel;
  87 #else
  88     using PmeKernelHandle = void*;
  89 #endif
  90
  91     /*! \brief
  92      * Maximum synchronous GPU thread group execution width.
  93      * "Warp" is a CUDA term which we end up reusing in OpenCL kernels as well.
  94      * For CUDA, this is a static value that comes from gromacs/gpu_utils/cuda_arch_utils.cuh;
  95      * for OpenCL, we have to query it dynamically.
  96      */
  97     size_t warpSize_;
  98
  99     //@{
 100     /**
 101      * Spread/spline kernels are compiled only for order of 4.
 102      * There are multiple versions of each kernel, paramaretized according to
 103      *   Number of threads per atom. Using either order(4) or order*order (16) threads per atom is
 104      * supported If the spline data is written in the spline/spread kernel and loaded in the gather
 105      *   or recalculated in the gather.
 106      * Spreading kernels also have hardcoded X/Y indices wrapping parameters,
 107      * as a placeholder for implementing 1/2D decomposition.
 108      * The kernels are templated separately for spreading on one grid (one or
 109      * two sets of coefficients) or on two grids (required for energy and virial
 110      * calculations).
 111      */
 112     size_t spreadWorkGroupSize;
 113
 114     PmeKernelHandle splineKernelSingle;
 115     PmeKernelHandle splineKernelThPerAtom4Single;
 116     PmeKernelHandle spreadKernelSingle;
 117     PmeKernelHandle spreadKernelThPerAtom4Single;
 118     PmeKernelHandle splineAndSpreadKernelSingle;
 119     PmeKernelHandle splineAndSpreadKernelThPerAtom4Single;
 120     PmeKernelHandle splineAndSpreadKernelWriteSplinesSingle;
 121     PmeKernelHandle splineAndSpreadKernelWriteSplinesThPerAtom4Single;
 122     PmeKernelHandle splineKernelDual;
 123     PmeKernelHandle splineKernelThPerAtom4Dual;
 124     PmeKernelHandle spreadKernelDual;
 125     PmeKernelHandle spreadKernelThPerAtom4Dual;
 126     PmeKernelHandle splineAndSpreadKernelDual;
 127     PmeKernelHandle splineAndSpreadKernelThPerAtom4Dual;
 128     PmeKernelHandle splineAndSpreadKernelWriteSplinesDual;
 129     PmeKernelHandle splineAndSpreadKernelWriteSplinesThPerAtom4Dual;
 130     //@}
 131
 132     //@{
 133     /** Same for gather: hardcoded X/Y unwrap parameters, order of 4, plus
 134      * it can either reduce with previous forces in the host buffer, or ignore them.
 135      * Also similarly to the gather we can use either order(4) or order*order (16) threads per atom
 136      * and either recalculate the splines or read the ones written by the spread
 137      * The kernels are templated separately for using one or two grids (required for
 138      * calculating energies and virial).
 139      */
 140     size_t gatherWorkGroupSize;
 141
 142     PmeKernelHandle gatherKernelSingle;
 143     PmeKernelHandle gatherKernelThPerAtom4Single;
 144     PmeKernelHandle gatherKernelReadSplinesSingle;
 145     PmeKernelHandle gatherKernelReadSplinesThPerAtom4Single;
 146     PmeKernelHandle gatherKernelDual;
 147     PmeKernelHandle gatherKernelThPerAtom4Dual;
 148     PmeKernelHandle gatherKernelReadSplinesDual;
 149     PmeKernelHandle gatherKernelReadSplinesThPerAtom4Dual;
 150     //@}
 151
 152     //@{
 153     /** Solve kernel doesn't care about the interpolation order, but can optionally
 154      * compute energy and virial, and supports XYZ and YZX grid orderings.
 155      * The kernels are templated separately for grids in state A and B.
 156      */
 157     size_t solveMaxWorkGroupSize;
 158
 159     PmeKernelHandle solveYZXKernelA;
 160     PmeKernelHandle solveXYZKernelA;
 161     PmeKernelHandle solveYZXEnergyKernelA;
 162     PmeKernelHandle solveXYZEnergyKernelA;
 163     PmeKernelHandle solveYZXKernelB;
 164     PmeKernelHandle solveXYZKernelB;
 165     PmeKernelHandle solveYZXEnergyKernelB;
 166     PmeKernelHandle solveXYZEnergyKernelB;
 167     //@}
 168
 169     PmeGpuProgramImpl() = delete;
 170     //! Constructor for the given device
 171     explicit PmeGpuProgramImpl(const DeviceContext& deviceContext);
 172     ~PmeGpuProgramImpl();
 173     GMX_DISALLOW_COPY_AND_ASSIGN(PmeGpuProgramImpl);
 174
 175     //! Return the warp size for which the kernels were compiled
 176     int warpSize() const { return warpSize_; }
 177
 178 private:
 179     // Compiles kernels, if supported. Called by the constructor.
 180     void compileKernels(const DeviceInformation& deviceInfo);
 181 };
 182
 183 #endif