/* -------------------------------------------------------------------------- * * OpenMM * * -------------------------------------------------------------------------- * * This is part of the OpenMM molecular simulation toolkit originating from * * Simbios, the NIH National Center for Physics-Based Simulation of * * Biological Structures at Stanford, funded under the NIH Roadmap for * * Medical Research, grant U54 GM072970. See https://simtk.org. * * * * Portions copyright (c) 2011-2024 Stanford University and the Authors. * * Authors: Peter Eastman * * Contributors: * * * * This program 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 3 of the License, or * * (at your option) any later version. * * * * This program 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 this program. If not, see . * * -------------------------------------------------------------------------- */ #include "OpenCLParallelKernels.h" #include "openmm/internal/timer.h" using namespace OpenMM; using namespace std; class OpenCLParallelCalcForcesAndEnergyKernel::BeginComputationTask : public OpenCLContext::WorkTask { public: BeginComputationTask(ContextImpl& context, OpenCLContext& cl, OpenCLCalcForcesAndEnergyKernel& kernel, bool includeForce, bool includeEnergy, int groups, void* pinnedMemory, int& numTiles) : context(context), cl(cl), kernel(kernel), includeForce(includeForce), includeEnergy(includeEnergy), groups(groups), pinnedMemory(pinnedMemory), numTiles(numTiles) { } void execute() { // Copy coordinates over to this device and execute the kernel. if (cl.getContextIndex() > 0) cl.getQueue().enqueueWriteBuffer(cl.getPosq().getDeviceBuffer(), CL_FALSE, 0, cl.getPaddedNumAtoms()*cl.getPosq().getElementSize(), pinnedMemory); kernel.beginComputation(context, includeForce, includeEnergy, groups); if (cl.getNonbondedUtilities().getUsePeriodic()) cl.getNonbondedUtilities().getInteractionCount().download(&numTiles, false); } private: ContextImpl& context; OpenCLContext& cl; OpenCLCalcForcesAndEnergyKernel& kernel; bool includeForce, includeEnergy; int groups; void* pinnedMemory; int& numTiles; }; class OpenCLParallelCalcForcesAndEnergyKernel::FinishComputationTask : public OpenCLContext::WorkTask { public: FinishComputationTask(ContextImpl& context, OpenCLContext& cl, OpenCLCalcForcesAndEnergyKernel& kernel, bool includeForce, bool includeEnergy, int groups, double& energy, double& completionTime, void* pinnedMemory, bool& valid, int& numTiles) : context(context), cl(cl), kernel(kernel), includeForce(includeForce), includeEnergy(includeEnergy), groups(groups), energy(energy), completionTime(completionTime), pinnedMemory(pinnedMemory), valid(valid), numTiles(numTiles) { } void execute() { // Execute the kernel, then download forces. energy += kernel.finishComputation(context, includeForce, includeEnergy, groups, valid); if (includeForce) { if (cl.getContextIndex() > 0) { int numAtoms = cl.getPaddedNumAtoms(); void* dest = (cl.getUseDoublePrecision() ? (void*) &((mm_double4*) pinnedMemory)[(cl.getContextIndex()-1)*numAtoms] : (void*) &((mm_float4*) pinnedMemory)[(cl.getContextIndex()-1)*numAtoms]); cl.getQueue().enqueueReadBuffer(cl.getForce().getDeviceBuffer(), CL_TRUE, 0, numAtoms*cl.getForce().getElementSize(), dest); } else cl.getQueue().finish(); } completionTime = getCurrentTime(); if (cl.getNonbondedUtilities().getUsePeriodic() && numTiles > cl.getNonbondedUtilities().getInteractingTiles().getSize()) { valid = false; cl.getNonbondedUtilities().updateNeighborListSize(); } } private: ContextImpl& context; OpenCLContext& cl; OpenCLCalcForcesAndEnergyKernel& kernel; bool includeForce, includeEnergy; int groups; double& energy; double& completionTime; void* pinnedMemory; bool& valid; int& numTiles; }; OpenCLParallelCalcForcesAndEnergyKernel::OpenCLParallelCalcForcesAndEnergyKernel(string name, const Platform& platform, OpenCLPlatform::PlatformData& data) : CalcForcesAndEnergyKernel(name, platform), data(data), completionTimes(data.contexts.size()), contextNonbondedFractions(data.contexts.size()), tileCounts(data.contexts.size()), pinnedPositionBuffer(NULL), pinnedPositionMemory(NULL), pinnedForceBuffer(NULL), pinnedForceMemory(NULL) { for (int i = 0; i < (int) data.contexts.size(); i++) kernels.push_back(Kernel(new OpenCLCalcForcesAndEnergyKernel(name, platform, *data.contexts[i]))); } OpenCLParallelCalcForcesAndEnergyKernel::~OpenCLParallelCalcForcesAndEnergyKernel() { if (pinnedPositionBuffer != NULL) delete pinnedPositionBuffer; if (pinnedForceBuffer != NULL) delete pinnedForceBuffer; } void OpenCLParallelCalcForcesAndEnergyKernel::initialize(const System& system) { for (int i = 0; i < (int) kernels.size(); i++) getKernel(i).initialize(system); for (int i = 0; i < contextNonbondedFractions.size(); i++) { double x0 = i/(double) contextNonbondedFractions.size(); double x1 = (i+1)/(double) contextNonbondedFractions.size(); contextNonbondedFractions[i] = x1*x1 - x0*x0; } } void OpenCLParallelCalcForcesAndEnergyKernel::beginComputation(ContextImpl& context, bool includeForce, bool includeEnergy, int groups) { OpenCLContext& cl0 = *data.contexts[0]; int elementSize = (cl0.getUseDoublePrecision() ? sizeof(mm_double4) : sizeof(mm_float4)); if (!contextForces.isInitialized()) { contextForces.initialize(cl0, &cl0.getForceBuffers().getDeviceBuffer(), data.contexts.size()*cl0.getPaddedNumAtoms(), "contextForces"); int bufferBytes = (data.contexts.size()-1)*cl0.getPaddedNumAtoms()*elementSize; pinnedPositionBuffer = new cl::Buffer(cl0.getContext(), CL_MEM_ALLOC_HOST_PTR, bufferBytes); pinnedPositionMemory = cl0.getQueue().enqueueMapBuffer(*pinnedPositionBuffer, CL_TRUE, CL_MAP_READ | CL_MAP_WRITE, 0, bufferBytes); pinnedForceBuffer = new cl::Buffer(cl0.getContext(), CL_MEM_ALLOC_HOST_PTR, bufferBytes); pinnedForceMemory = cl0.getQueue().enqueueMapBuffer(*pinnedForceBuffer, CL_TRUE, CL_MAP_READ | CL_MAP_WRITE, 0, bufferBytes); } // Copy coordinates over to each device and execute the kernel. cl0.getQueue().enqueueReadBuffer(cl0.getPosq().getDeviceBuffer(), CL_TRUE, 0, cl0.getPaddedNumAtoms()*elementSize, pinnedPositionMemory); for (int i = 0; i < (int) data.contexts.size(); i++) { data.contextEnergy[i] = 0.0; OpenCLContext& cl = *data.contexts[i]; ComputeContext::WorkThread& thread = cl.getWorkThread(); thread.addTask(new BeginComputationTask(context, cl, getKernel(i), includeForce, includeEnergy, groups, pinnedPositionMemory, tileCounts[i])); } } double OpenCLParallelCalcForcesAndEnergyKernel::finishComputation(ContextImpl& context, bool includeForce, bool includeEnergy, int groups, bool& valid) { for (int i = 0; i < (int) data.contexts.size(); i++) { OpenCLContext& cl = *data.contexts[i]; ComputeContext::WorkThread& thread = cl.getWorkThread(); thread.addTask(new FinishComputationTask(context, cl, getKernel(i), includeForce, includeEnergy, groups, data.contextEnergy[i], completionTimes[i], pinnedForceMemory, valid, tileCounts[i])); } data.syncContexts(); double energy = 0.0; for (int i = 0; i < (int) data.contextEnergy.size(); i++) energy += data.contextEnergy[i]; if (includeForce && valid) { // Sum the forces from all devices. OpenCLContext& cl = *data.contexts[0]; int numAtoms = cl.getPaddedNumAtoms(); int elementSize = (cl.getUseDoublePrecision() ? sizeof(mm_double4) : sizeof(mm_float4)); cl.getQueue().enqueueWriteBuffer(contextForces.getDeviceBuffer(), CL_FALSE, numAtoms*elementSize, numAtoms*(data.contexts.size()-1)*elementSize, pinnedForceMemory); cl.reduceBuffer(contextForces, cl.getLongForceBuffer(), data.contexts.size()); // Balance work between the contexts by transferring a little nonbonded work from the context that // finished last to the one that finished first. if (cl.getComputeForceCount() < 200 || cl.getComputeForceCount()%30 == 0) { int firstIndex = 0, lastIndex = 0; for (int i = 0; i < (int) completionTimes.size(); i++) { if (completionTimes[i] < completionTimes[firstIndex]) firstIndex = i; if (completionTimes[i] > completionTimes[lastIndex]) lastIndex = i; } double fractionToTransfer = min(0.001, contextNonbondedFractions[lastIndex]); contextNonbondedFractions[firstIndex] += fractionToTransfer; contextNonbondedFractions[lastIndex] -= fractionToTransfer; double startFraction = 0.0; for (int i = 0; i < (int) contextNonbondedFractions.size(); i++) { double endFraction = startFraction+contextNonbondedFractions[i]; if (i == contextNonbondedFractions.size()-1) endFraction = 1.0; // Avoid roundoff error data.contexts[i]->getNonbondedUtilities().setAtomBlockRange(startFraction, endFraction); startFraction = endFraction; } } } return energy; } class OpenCLParallelCalcNonbondedForceKernel::Task : public OpenCLContext::WorkTask { public: Task(ContextImpl& context, OpenCLCalcNonbondedForceKernel& kernel, bool includeForce, bool includeEnergy, bool includeDirect, bool includeReciprocal, double& energy) : context(context), kernel(kernel), includeForce(includeForce), includeEnergy(includeEnergy), includeDirect(includeDirect), includeReciprocal(includeReciprocal), energy(energy) { } void execute() { energy += kernel.execute(context, includeForce, includeEnergy, includeDirect, includeReciprocal); } private: ContextImpl& context; OpenCLCalcNonbondedForceKernel& kernel; bool includeForce, includeEnergy, includeDirect, includeReciprocal; double& energy; }; OpenCLParallelCalcNonbondedForceKernel::OpenCLParallelCalcNonbondedForceKernel(std::string name, const Platform& platform, OpenCLPlatform::PlatformData& data, const System& system) : CalcNonbondedForceKernel(name, platform), data(data) { for (int i = 0; i < (int) data.contexts.size(); i++) kernels.push_back(Kernel(new OpenCLCalcNonbondedForceKernel(name, platform, *data.contexts[i], system))); } void OpenCLParallelCalcNonbondedForceKernel::initialize(const System& system, const NonbondedForce& force) { for (int i = 0; i < (int) kernels.size(); i++) getKernel(i).initialize(system, force); } double OpenCLParallelCalcNonbondedForceKernel::execute(ContextImpl& context, bool includeForces, bool includeEnergy, bool includeDirect, bool includeReciprocal) { for (int i = 0; i < (int) data.contexts.size(); i++) { OpenCLContext& cl = *data.contexts[i]; ComputeContext::WorkThread& thread = cl.getWorkThread(); thread.addTask(new Task(context, getKernel(i), includeForces, includeEnergy, includeDirect, includeReciprocal, data.contextEnergy[i])); } return 0.0; } void OpenCLParallelCalcNonbondedForceKernel::copyParametersToContext(ContextImpl& context, const NonbondedForce& force, int firstParticle, int lastParticle, int firstException, int lastException) { for (int i = 0; i < (int) kernels.size(); i++) getKernel(i).copyParametersToContext(context, force, firstParticle, lastParticle, firstException, lastException); } void OpenCLParallelCalcNonbondedForceKernel::getPMEParameters(double& alpha, int& nx, int& ny, int& nz) const { dynamic_cast(kernels[0].getImpl()).getPMEParameters(alpha, nx, ny, nz); } void OpenCLParallelCalcNonbondedForceKernel::getLJPMEParameters(double& alpha, int& nx, int& ny, int& nz) const { dynamic_cast(kernels[0].getImpl()).getLJPMEParameters(alpha, nx, ny, nz); }