Gromacs
2022.2
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#include <gromacs/ewald/pme_gpu_program_impl.h>
PME GPU persistent host program/kernel data, which should be initialized once for the whole execution.
Primary purpose of this is to not recompile GPU kernels for each OpenCL unit test, while the relevant GPU context (e.g. cl_context) instance persists. In CUDA, this just assigns the kernel function pointers. This also implicitly relies on the fact that reasonable share of the kernels are always used. If there were more template parameters, even smaller share of all possible kernels would be used.
This also doesn't manage cuFFT/clFFT kernels, which depend on the PME grid dimensions.
TODO: pass cl_context to the constructor and not create it inside. See also Issue #2522.
Public Types | |
using | PmeKernelHandle = ISyclKernelFunctor * |
Conveniently all the PME kernels use the same single argument type. | |
Public Member Functions | |
PmeGpuProgramImpl (const DeviceContext &deviceContext) | |
Constructor for the given device. | |
int | warpSize () const |
Return the warp size for which the kernels were compiled. | |
Public Attributes | |
const DeviceContext & | deviceContext_ |
This is a handle to the GPU context, which is just a dummy in CUDA, but is created/destroyed by this class in OpenCL. | |
size_t | warpSize_ |
Maximum synchronous GPU thread group execution width. "Warp" is a CUDA term which we end up reusing in OpenCL kernels as well. For CUDA, this is a static value that comes from gromacs/gpu_utils/cuda_arch_utils.cuh; for OpenCL, we have to query it dynamically. | |
size_t | spreadWorkGroupSize |
Spread/spline kernels are compiled only for order of 4. More... | |
PmeKernelHandle | splineKernelSingle |
PmeKernelHandle | splineKernelThPerAtom4Single |
PmeKernelHandle | spreadKernelSingle |
PmeKernelHandle | spreadKernelThPerAtom4Single |
PmeKernelHandle | splineAndSpreadKernelSingle |
PmeKernelHandle | splineAndSpreadKernelThPerAtom4Single |
PmeKernelHandle | splineAndSpreadKernelWriteSplinesSingle |
PmeKernelHandle | splineAndSpreadKernelWriteSplinesThPerAtom4Single |
PmeKernelHandle | splineKernelDual |
PmeKernelHandle | splineKernelThPerAtom4Dual |
PmeKernelHandle | spreadKernelDual |
PmeKernelHandle | spreadKernelThPerAtom4Dual |
PmeKernelHandle | splineAndSpreadKernelDual |
PmeKernelHandle | splineAndSpreadKernelThPerAtom4Dual |
PmeKernelHandle | splineAndSpreadKernelWriteSplinesDual |
PmeKernelHandle | splineAndSpreadKernelWriteSplinesThPerAtom4Dual |
size_t | gatherWorkGroupSize |
Same for gather: hardcoded X/Y unwrap parameters, order of 4, plus it can either reduce with previous forces in the host buffer, or ignore them. More... | |
PmeKernelHandle | gatherKernelSingle |
PmeKernelHandle | gatherKernelThPerAtom4Single |
PmeKernelHandle | gatherKernelReadSplinesSingle |
PmeKernelHandle | gatherKernelReadSplinesThPerAtom4Single |
PmeKernelHandle | gatherKernelDual |
PmeKernelHandle | gatherKernelThPerAtom4Dual |
PmeKernelHandle | gatherKernelReadSplinesDual |
PmeKernelHandle | gatherKernelReadSplinesThPerAtom4Dual |
size_t | solveMaxWorkGroupSize |
Solve kernel doesn't care about the interpolation order, but can optionally compute energy and virial, and supports XYZ and YZX grid orderings. More... | |
PmeKernelHandle | solveYZXKernelA |
PmeKernelHandle | solveXYZKernelA |
PmeKernelHandle | solveYZXEnergyKernelA |
PmeKernelHandle | solveXYZEnergyKernelA |
PmeKernelHandle | solveYZXKernelB |
PmeKernelHandle | solveXYZKernelB |
PmeKernelHandle | solveYZXEnergyKernelB |
PmeKernelHandle | solveXYZEnergyKernelB |
size_t PmeGpuProgramImpl::gatherWorkGroupSize |
Same for gather: hardcoded X/Y unwrap parameters, order of 4, plus it can either reduce with previous forces in the host buffer, or ignore them.
Also similarly to the gather we can use either order(4) or order*order (16) threads per atom and either recalculate the splines or read the ones written by the spread The kernels are templated separately for using one or two grids (required for calculating energies and virial).
size_t PmeGpuProgramImpl::solveMaxWorkGroupSize |
Solve kernel doesn't care about the interpolation order, but can optionally compute energy and virial, and supports XYZ and YZX grid orderings.
The kernels are templated separately for grids in state A and B.
size_t PmeGpuProgramImpl::spreadWorkGroupSize |
Spread/spline kernels are compiled only for order of 4.
There are multiple versions of each kernel, paramaretized according to Number of threads per atom. Using either order(4) or order*order (16) threads per atom is supported If the spline data is written in the spline/spread kernel and loaded in the gather or recalculated in the gather. Spreading kernels also have hardcoded X/Y indices wrapping parameters, as a placeholder for implementing 1/2D decomposition. The kernels are templated separately for spreading on one grid (one or two sets of coefficients) or on two grids (required for energy and virial calculations).