/* -------------------------------------------------------------------------- * * 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) 2009 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 . * * -------------------------------------------------------------------------- */ #ifdef WIN32 #define _USE_MATH_DEFINES // Needed to get M_PI #endif #include #include "OpenCLContext.h" #include "OpenCLArray.h" #include "OpenCLBondedUtilities.h" #include "OpenCLForceInfo.h" #include "OpenCLIntegrationUtilities.h" #include "OpenCLKernelSources.h" #include "OpenCLNonbondedUtilities.h" #include "hilbert.h" #include "openmm/Platform.h" #include "openmm/System.h" #include "openmm/VirtualSite.h" #include #include #include #include #include using namespace OpenMM; using namespace std; #ifndef CL_DEVICE_COMPUTE_CAPABILITY_MAJOR_NV #define CL_DEVICE_COMPUTE_CAPABILITY_MAJOR_NV 0x4000 #endif #ifndef CL_DEVICE_COMPUTE_CAPABILITY_MINOR_NV #define CL_DEVICE_COMPUTE_CAPABILITY_MINOR_NV 0x4001 #endif const int OpenCLContext::ThreadBlockSize = 64; const int OpenCLContext::TileSize = 32; static void CL_CALLBACK errorCallback(const char* errinfo, const void* private_info, size_t cb, void* user_data) { string skip = "OpenCL Build Warning : Compiler build log:"; if (strncmp(errinfo, skip.c_str(), skip.length()) == 0) return; // OS X Lion insists on calling this for every build warning, even though they aren't errors. std::cerr << "OpenCL internal error: " << errinfo << std::endl; } OpenCLContext::OpenCLContext(int numParticles, int platformIndex, int deviceIndex, OpenCLPlatform::PlatformData& platformData) : time(0.0), platformData(platformData), stepCount(0), computeForceCount(0), atomsWereReordered(false), posq(NULL), velm(NULL), forceBuffers(NULL), longForceBuffer(NULL), energyBuffer(NULL), atomIndex(NULL), integration(NULL), bonded(NULL), nonbonded(NULL), thread(NULL) { try { contextIndex = platformData.contexts.size(); std::vector platforms; cl::Platform::get(&platforms); if (platformIndex < 0 || platformIndex >= platforms.size()) throw OpenMMException("Illegal value for OpenCL platform index"); vector devices; platforms[platformIndex].getDevices(CL_DEVICE_TYPE_ALL, &devices); const int minThreadBlockSize = 32; if (deviceIndex < 0 || deviceIndex >= (int) devices.size()) { // Try to figure out which device is the fastest. int bestSpeed = -1; for (int i = 0; i < (int) devices.size(); i++) { if (platforms[platformIndex].getInfo() == "Apple" && devices[i].getInfo() == "AMD") continue; // Don't use AMD GPUs on OS X due to serious bugs. int maxSize = devices[i].getInfo()[0]; int processingElementsPerComputeUnit = 8; if (devices[i].getInfo() != CL_DEVICE_TYPE_GPU) { processingElementsPerComputeUnit = 1; } else if (devices[i].getInfo().find("cl_nv_device_attribute_query") != string::npos) { cl_uint computeCapabilityMajor; clGetDeviceInfo(devices[i](), CL_DEVICE_COMPUTE_CAPABILITY_MAJOR_NV, sizeof(cl_uint), &computeCapabilityMajor, NULL); processingElementsPerComputeUnit = (computeCapabilityMajor < 2 ? 8 : 32); } else if (devices[i].getInfo().find("cl_amd_device_attribute_query") != string::npos) { // This attribute does not ensure that all queries are supported by the runtime (it may be an older runtime, // or the CPU device) so still have to check for errors. try { processingElementsPerComputeUnit = // AMD GPUs either have a single VLIW SIMD or multiple scalar SIMDs. // The SIMD width is the number of threads the SIMD executes per cycle. // This will be less than the wavefront width since it takes several // cycles to execute the full wavefront. // The SIMD instruction width is the VLIW instruction width (or 1 for scalar), // this is the number of ALUs that can be executing per instruction per thread. devices[i].getInfo() * devices[i].getInfo() * devices[i].getInfo(); // Just in case any of the queries return 0. if (processingElementsPerComputeUnit <= 0) processingElementsPerComputeUnit = 1; } catch (cl::Error err) { // Runtime does not support the queries so use default. } } int speed = devices[i].getInfo()*processingElementsPerComputeUnit*devices[i].getInfo(); if (maxSize >= minThreadBlockSize && speed > bestSpeed) { deviceIndex = i; bestSpeed = speed; } } } if (deviceIndex == -1) throw OpenMMException("No compatible OpenCL device is available"); device = devices[deviceIndex]; this->deviceIndex = deviceIndex; if (device.getInfo() < minThreadBlockSize) throw OpenMMException("The specified OpenCL device is not compatible with OpenMM"); compilationDefines["WORK_GROUP_SIZE"] = OpenCLExpressionUtilities::intToString(ThreadBlockSize); defaultOptimizationOptions = "-cl-fast-relaxed-math"; supports64BitGlobalAtomics = (device.getInfo().find("cl_khr_int64_base_atomics") != string::npos); supportsDoublePrecision = (device.getInfo().find("cl_khr_fp64") != string::npos); string vendor = device.getInfo(); int numThreadBlocksPerComputeUnit = 6; if (vendor.size() >= 6 && vendor.substr(0, 6) == "NVIDIA") { compilationDefines["WARPS_ARE_ATOMIC"] = ""; simdWidth = 32; if (device.getInfo().find("cl_nv_device_attribute_query") != string::npos) { // Compute level 1.2 and later Nvidia GPUs support 64 bit atomics, even though they don't list the // proper extension as supported. We only use them on compute level 2.0 or later, since they're very // slow on earlier GPUs. cl_uint computeCapabilityMajor; clGetDeviceInfo(device(), CL_DEVICE_COMPUTE_CAPABILITY_MAJOR_NV, sizeof(cl_uint), &computeCapabilityMajor, NULL); if (computeCapabilityMajor > 1) supports64BitGlobalAtomics = true; } } else if (vendor.size() >= 28 && vendor.substr(0, 28) == "Advanced Micro Devices, Inc.") { // Disable 64 bit atomics. A future version of the driver will support them, but until we can test that, // it's safest not to use them. supports64BitGlobalAtomics = false; if (device.getInfo() != CL_DEVICE_TYPE_GPU) { /// \todo Is 6 a good value for the OpenCL CPU device? // numThreadBlocksPerComputeUnit = ?; simdWidth = 1; } else { bool amdPostSdk2_4 = false; // Default to 1 which will use the default kernels. simdWidth = 1; if (device.getInfo().find("cl_amd_device_attribute_query") != string::npos) { // This attribute does not ensure that all queries are supported by the runtime so still have to // check for errors. try { // AMD has both 32 and 64 width SIMDs. Can determine by using: // simdWidth = device.getInfo(); // Must catch cl:Error as will fail if runtime does not support queries. // However, the 32 width NVIDIA kernels do not have all the necessary // barriers and so will not work for AMD. // So for now leave default of 1 which will use the default kernels. cl_uint simdPerComputeUnit = device.getInfo(); // If the GPU has multiple SIMDs per compute unit then it is uses the scalar instruction // set instead of the VLIW instruction set. It therefore needs more thread blocks per // compute unit to hide memory latency. if (simdPerComputeUnit > 1) numThreadBlocksPerComputeUnit = 4 * simdPerComputeUnit; // If the queries are supported then must be newer than SDK 2.4. amdPostSdk2_4 = true; } catch (cl::Error err) { // Runtime does not support the query so is unlikely to be the newer scalar GPU. // Stay with the default simdWidth and numThreadBlocksPerComputeUnit. } } // AMD APP SDK 2.4 has a performance problem with atomics. Enable the work around. This is fixed after SDK 2.4. if (!amdPostSdk2_4) compilationDefines["AMD_ATOMIC_WORK_AROUND"] = ""; } } else simdWidth = 1; if (platforms[platformIndex].getInfo() == "Apple" && vendor == "AMD") compilationDefines["MAC_AMD_WORKAROUND"] = ""; if (supports64BitGlobalAtomics) compilationDefines["SUPPORTS_64_BIT_ATOMICS"] = ""; if (supportsDoublePrecision) compilationDefines["SUPPORTS_DOUBLE_PRECISION"] = ""; vector contextDevices; contextDevices.push_back(device); cl_context_properties cprops[] = {CL_CONTEXT_PLATFORM, (cl_context_properties) platforms[platformIndex](), 0}; context = cl::Context(contextDevices, cprops, errorCallback); queue = cl::CommandQueue(context, device); numAtoms = numParticles; paddedNumAtoms = TileSize*((numParticles+TileSize-1)/TileSize); numAtomBlocks = (paddedNumAtoms+(TileSize-1))/TileSize; numThreadBlocks = numThreadBlocksPerComputeUnit*device.getInfo(); bonded = new OpenCLBondedUtilities(*this); nonbonded = new OpenCLNonbondedUtilities(*this); posq = new OpenCLArray(*this, paddedNumAtoms, "posq", true); velm = new OpenCLArray(*this, paddedNumAtoms, "velm", true); posCellOffsets.resize(paddedNumAtoms, mm_int4(0, 0, 0, 0)); } catch (cl::Error err) { std::stringstream str; str<<"Error initializing context: "< values(*this, 20, "values", true); float nextValue = 1e-4f; for (int i = 0; i < values.getSize(); ++i) { values[i].s0 = nextValue; nextValue *= (float) M_PI; } values.upload(); accuracyKernel.setArg(0, values.getDeviceBuffer()); accuracyKernel.setArg(1, values.getSize()); executeKernel(accuracyKernel, values.getSize()); values.download(); double maxSqrtError = 0.0, maxRsqrtError = 0.0, maxRecipError = 0.0, maxExpError = 0.0, maxLogError = 0.0; for (int i = 0; i < values.getSize(); ++i) { double v = values[i].s0; double correctSqrt = sqrt(v); maxSqrtError = max(maxSqrtError, fabs(correctSqrt-values[i].s1)/correctSqrt); maxRsqrtError = max(maxRsqrtError, fabs(1.0/correctSqrt-values[i].s2)*correctSqrt); maxRecipError = max(maxRecipError, fabs(1.0/v-values[i].s3)/values[i].s3); maxExpError = max(maxExpError, fabs(exp(v)-values[i].s4)/values[i].s4); maxLogError = max(maxLogError, fabs(log(v)-values[i].s5)/values[i].s5); } compilationDefines["SQRT"] = (maxSqrtError < 1e-6) ? "native_sqrt" : "sqrt"; compilationDefines["RSQRT"] = (maxRsqrtError < 1e-6) ? "native_rsqrt" : "rsqrt"; compilationDefines["RECIP"] = (maxRecipError < 1e-6) ? "native_recip" : "1.0f/"; compilationDefines["EXP"] = (maxExpError < 1e-6) ? "native_exp" : "exp"; compilationDefines["LOG"] = (maxLogError < 1e-6) ? "native_log" : "log"; // Create the work thread used for parallelization when running on multiple devices. thread = new WorkThread(); } OpenCLContext::~OpenCLContext() { for (int i = 0; i < (int) forces.size(); i++) delete forces[i]; for (int i = 0; i < (int) reorderListeners.size(); i++) delete reorderListeners[i]; if (posq != NULL) delete posq; if (velm != NULL) delete velm; if (force != NULL) delete force; if (forceBuffers != NULL) delete forceBuffers; if (longForceBuffer != NULL) delete longForceBuffer; if (energyBuffer != NULL) delete energyBuffer; if (atomIndex != NULL) delete atomIndex; if (integration != NULL) delete integration; if (bonded != NULL) delete bonded; if (nonbonded != NULL) delete nonbonded; if (thread != NULL) delete thread; } void OpenCLContext::initialize(const System& system) { for (int i = 0; i < numAtoms; i++) { double mass = system.getParticleMass(i); (*velm)[i].w = (float) (mass == 0.0 ? 0.0 : 1.0/mass); } velm->upload(); bonded->initialize(system); numForceBuffers = platformData.contexts.size(); numForceBuffers = std::max(numForceBuffers, bonded->getNumForceBuffers()); for (int i = 0; i < (int) forces.size(); i++) numForceBuffers = std::max(numForceBuffers, forces[i]->getRequiredForceBuffers()); forceBuffers = new OpenCLArray(*this, paddedNumAtoms*numForceBuffers, "forceBuffers", false); if (supports64BitGlobalAtomics) { longForceBuffer = new OpenCLArray(*this, 3*paddedNumAtoms, "longForceBuffer", false); reduceForcesKernel.setArg(0, longForceBuffer->getDeviceBuffer()); reduceForcesKernel.setArg(1, forceBuffers->getDeviceBuffer()); reduceForcesKernel.setArg(2, paddedNumAtoms); reduceForcesKernel.setArg(3, numForceBuffers); addAutoclearBuffer(longForceBuffer->getDeviceBuffer(), longForceBuffer->getSize()*2); } addAutoclearBuffer(forceBuffers->getDeviceBuffer(), forceBuffers->getSize()*4); force = new OpenCLArray(*this, &forceBuffers->getDeviceBuffer(), paddedNumAtoms, "force", true); energyBuffer = new OpenCLArray(*this, max(numThreadBlocks*ThreadBlockSize, nonbonded->getNumEnergyBuffers()), "energyBuffer", true); addAutoclearBuffer(energyBuffer->getDeviceBuffer(), energyBuffer->getSize()); atomIndex = new OpenCLArray(*this, paddedNumAtoms, "atomIndex", true); for (int i = 0; i < paddedNumAtoms; ++i) (*atomIndex)[i] = i; atomIndex->upload(); findMoleculeGroups(system); integration = new OpenCLIntegrationUtilities(*this, system); nonbonded->initialize(system); } void OpenCLContext::addForce(OpenCLForceInfo* force) { forces.push_back(force); } string OpenCLContext::loadSourceFromFile(const string& filename) const { ifstream file((Platform::getDefaultPluginsDirectory()+"/opencl/"+filename).c_str()); if (!file.is_open()) throw OpenMMException("Unable to load kernel: "+filename); string kernel; string line; while (!file.eof()) { getline(file, line); kernel += line; kernel += '\n'; } file.close(); return kernel; } string OpenCLContext::loadSourceFromFile(const string& filename, const std::map& replacements) const { return replaceStrings(loadSourceFromFile(filename), replacements); } string OpenCLContext::replaceStrings(const string& input, const std::map& replacements) const { string result = input; for (map::const_iterator iter = replacements.begin(); iter != replacements.end(); iter++) { int index = -1; do { index = result.find(iter->first); if (index != result.npos) result.replace(index, iter->first.size(), iter->second); } while (index != result.npos); } return result; } cl::Program OpenCLContext::createProgram(const string source, const char* optimizationFlags) { return createProgram(source, map(), optimizationFlags); } cl::Program OpenCLContext::createProgram(const string source, const map& defines, const char* optimizationFlags) { string options = (optimizationFlags == NULL ? defaultOptimizationOptions : optimizationFlags); stringstream src; if (!options.empty()) src << "// Compilation Options: " << options << endl << endl; for (map::const_iterator iter = compilationDefines.begin(); iter != compilationDefines.end(); ++iter) { src << "#define " << iter->first; if (!iter->second.empty()) src << " " << iter->second; src << endl; } if (!compilationDefines.empty()) src << endl; for (map::const_iterator iter = defines.begin(); iter != defines.end(); ++iter) { src << "#define " << iter->first; if (!iter->second.empty()) src << " " << iter->second; src << endl; } if (!defines.empty()) src << endl; src << source << endl; // Get length before using c_str() to avoid length() call invalidating the c_str() value. string src_string = src.str(); ::size_t src_length = src_string.length(); cl::Program::Sources sources(1, make_pair(src_string.c_str(), src_length)); cl::Program program(context, sources); try { program.build(vector(1, device), options.c_str()); } catch (cl::Error err) { throw OpenMMException("Error compiling kernel: "+program.getBuildInfo(device)); } return program; } void OpenCLContext::executeKernel(cl::Kernel& kernel, int workUnits, int blockSize) { if (blockSize == -1) blockSize = ThreadBlockSize; int size = std::min((workUnits+blockSize-1)/blockSize, numThreadBlocks)*blockSize; try { queue.enqueueNDRangeKernel(kernel, cl::NullRange, cl::NDRange(size), cl::NDRange(blockSize)); } catch (cl::Error err) { stringstream str; str<<"Error invoking kernel "<()<<": "<& array) { clearBuffer(array.getDeviceBuffer(), array.getSize()); } void OpenCLContext::clearBuffer(OpenCLArray& array) { clearBuffer(array.getDeviceBuffer(), array.getSize()*4); } void OpenCLContext::clearBuffer(cl::Memory& memory, int size) { clearBufferKernel.setArg(0, memory); clearBufferKernel.setArg(1, size); executeKernel(clearBufferKernel, size, 128); } void OpenCLContext::addAutoclearBuffer(cl::Memory& memory, int size) { autoclearBuffers.push_back(&memory); autoclearBufferSizes.push_back(size); } void OpenCLContext::clearAutoclearBuffers() { int base = 0; int total = autoclearBufferSizes.size(); while (total-base >= 6) { clearSixBuffersKernel.setArg(0, *autoclearBuffers[base]); clearSixBuffersKernel.setArg(1, autoclearBufferSizes[base]); clearSixBuffersKernel.setArg(2, *autoclearBuffers[base+1]); clearSixBuffersKernel.setArg(3, autoclearBufferSizes[base+1]); clearSixBuffersKernel.setArg(4, *autoclearBuffers[base+2]); clearSixBuffersKernel.setArg(5, autoclearBufferSizes[base+2]); clearSixBuffersKernel.setArg(6, *autoclearBuffers[base+3]); clearSixBuffersKernel.setArg(7, autoclearBufferSizes[base+3]); clearSixBuffersKernel.setArg(8, *autoclearBuffers[base+4]); clearSixBuffersKernel.setArg(9, autoclearBufferSizes[base+4]); clearSixBuffersKernel.setArg(10, *autoclearBuffers[base+5]); clearSixBuffersKernel.setArg(11, autoclearBufferSizes[base+5]); executeKernel(clearSixBuffersKernel, max(max(max(max(max(autoclearBufferSizes[base], autoclearBufferSizes[base+1]), autoclearBufferSizes[base+2]), autoclearBufferSizes[base+3]), autoclearBufferSizes[base+4]), autoclearBufferSizes[base+5]), 128); base += 6; } if (total-base == 5) { clearFiveBuffersKernel.setArg(0, *autoclearBuffers[base]); clearFiveBuffersKernel.setArg(1, autoclearBufferSizes[base]); clearFiveBuffersKernel.setArg(2, *autoclearBuffers[base+1]); clearFiveBuffersKernel.setArg(3, autoclearBufferSizes[base+1]); clearFiveBuffersKernel.setArg(4, *autoclearBuffers[base+2]); clearFiveBuffersKernel.setArg(5, autoclearBufferSizes[base+2]); clearFiveBuffersKernel.setArg(6, *autoclearBuffers[base+3]); clearFiveBuffersKernel.setArg(7, autoclearBufferSizes[base+3]); clearFiveBuffersKernel.setArg(8, *autoclearBuffers[base+4]); clearFiveBuffersKernel.setArg(9, autoclearBufferSizes[base+4]); executeKernel(clearFiveBuffersKernel, max(max(max(max(autoclearBufferSizes[base], autoclearBufferSizes[base+1]), autoclearBufferSizes[base+2]), autoclearBufferSizes[base+3]), autoclearBufferSizes[base+4]), 128); } else if (total-base == 4) { clearFourBuffersKernel.setArg(0, *autoclearBuffers[base]); clearFourBuffersKernel.setArg(1, autoclearBufferSizes[base]); clearFourBuffersKernel.setArg(2, *autoclearBuffers[base+1]); clearFourBuffersKernel.setArg(3, autoclearBufferSizes[base+1]); clearFourBuffersKernel.setArg(4, *autoclearBuffers[base+2]); clearFourBuffersKernel.setArg(5, autoclearBufferSizes[base+2]); clearFourBuffersKernel.setArg(6, *autoclearBuffers[base+3]); clearFourBuffersKernel.setArg(7, autoclearBufferSizes[base+3]); executeKernel(clearFourBuffersKernel, max(max(max(autoclearBufferSizes[base], autoclearBufferSizes[base+1]), autoclearBufferSizes[base+2]), autoclearBufferSizes[base+3]), 128); } else if (total-base == 3) { clearThreeBuffersKernel.setArg(0, *autoclearBuffers[base]); clearThreeBuffersKernel.setArg(1, autoclearBufferSizes[base]); clearThreeBuffersKernel.setArg(2, *autoclearBuffers[base+1]); clearThreeBuffersKernel.setArg(3, autoclearBufferSizes[base+1]); clearThreeBuffersKernel.setArg(4, *autoclearBuffers[base+2]); clearThreeBuffersKernel.setArg(5, autoclearBufferSizes[base+2]); executeKernel(clearThreeBuffersKernel, max(max(autoclearBufferSizes[base], autoclearBufferSizes[base+1]), autoclearBufferSizes[base+2]), 128); } else if (total-base == 2) { clearTwoBuffersKernel.setArg(0, *autoclearBuffers[base]); clearTwoBuffersKernel.setArg(1, autoclearBufferSizes[base]); clearTwoBuffersKernel.setArg(2, *autoclearBuffers[base+1]); clearTwoBuffersKernel.setArg(3, autoclearBufferSizes[base+1]); executeKernel(clearTwoBuffersKernel, max(autoclearBufferSizes[base], autoclearBufferSizes[base+1]), 128); } else if (total-base == 1) { clearBuffer(*autoclearBuffers[base], autoclearBufferSizes[base]); } } void OpenCLContext::reduceForces() { if (supports64BitGlobalAtomics) executeKernel(reduceForcesKernel, paddedNumAtoms, 128); else reduceBuffer(*forceBuffers, numForceBuffers); } void OpenCLContext::reduceBuffer(OpenCLArray& array, int numBuffers) { int bufferSize = array.getSize()/numBuffers; reduceFloat4Kernel.setArg(0, array.getDeviceBuffer()); reduceFloat4Kernel.setArg(1, bufferSize); reduceFloat4Kernel.setArg(2, numBuffers); executeKernel(reduceFloat4Kernel, bufferSize, 128); } void OpenCLContext::tagAtomsInMolecule(int atom, int molecule, vector& atomMolecule, vector >& atomBonds) { // Recursively tag atoms as belonging to a particular molecule. atomMolecule[atom] = molecule; for (int i = 0; i < (int) atomBonds[atom].size(); i++) if (atomMolecule[atomBonds[atom][i]] == -1) tagAtomsInMolecule(atomBonds[atom][i], molecule, atomMolecule, atomBonds); } struct OpenCLContext::Molecule { vector atoms; vector constraints; vector > groups; }; /** * This class ensures that atom reordering doesn't break virtual sites. */ class OpenCLContext::VirtualSiteInfo : public OpenCLForceInfo { public: VirtualSiteInfo(const System& system) : OpenCLForceInfo(0) { for (int i = 0; i < system.getNumParticles(); i++) { if (system.isVirtualSite(i)) { siteTypes.push_back(&typeid(system.getVirtualSite(i))); vector particles; particles.push_back(i); for (int j = 0; j < system.getVirtualSite(i).getNumParticles(); j++) particles.push_back(system.getVirtualSite(i).getParticle(j)); siteParticles.push_back(particles); vector weights; if (dynamic_cast(&system.getVirtualSite(i)) != NULL) { // A two particle average. const TwoParticleAverageSite& site = dynamic_cast(system.getVirtualSite(i)); weights.push_back(site.getWeight(0)); weights.push_back(site.getWeight(1)); } else if (dynamic_cast(&system.getVirtualSite(i)) != NULL) { // A three particle average. const ThreeParticleAverageSite& site = dynamic_cast(system.getVirtualSite(i)); weights.push_back(site.getWeight(0)); weights.push_back(site.getWeight(1)); weights.push_back(site.getWeight(2)); } else if (dynamic_cast(&system.getVirtualSite(i)) != NULL) { // An out of plane site. const OutOfPlaneSite& site = dynamic_cast(system.getVirtualSite(i)); weights.push_back(site.getWeight12()); weights.push_back(site.getWeight13()); weights.push_back(site.getWeightCross()); } siteWeights.push_back(weights); } } } int getNumParticleGroups() { return siteTypes.size(); } void getParticlesInGroup(int index, std::vector& particles) { particles = siteParticles[index]; } bool areGroupsIdentical(int group1, int group2) { if (siteTypes[group1] != siteTypes[group2]) return false; int numParticles = siteWeights[group1].size(); if (siteWeights[group2].size() != numParticles) return false; for (int i = 0; i < numParticles; i++) if (siteWeights[group1][i] != siteWeights[group2][i]) return false; return true; } private: vector siteTypes; vector > siteParticles; vector > siteWeights; }; void OpenCLContext::findMoleculeGroups(const System& system) { // Add a ForceInfo that makes sure reordering doesn't break virtual sites. addForce(new VirtualSiteInfo(system)); // First make a list of every other atom to which each atom is connect by a constraint or force group. vector > atomBonds(system.getNumParticles()); for (int i = 0; i < system.getNumConstraints(); i++) { int particle1, particle2; double distance; system.getConstraintParameters(i, particle1, particle2, distance); atomBonds[particle1].push_back(particle2); atomBonds[particle2].push_back(particle1); } for (int i = 0; i < (int) forces.size(); i++) { for (int j = 0; j < forces[i]->getNumParticleGroups(); j++) { vector particles; forces[i]->getParticlesInGroup(j, particles); for (int k = 0; k < (int) particles.size(); k++) for (int m = 0; m < (int) particles.size(); m++) if (k != m) atomBonds[particles[k]].push_back(particles[m]); } } // Now tag atoms by which molecule they belong to. vector atomMolecule(numAtoms, -1); int numMolecules = 0; for (int i = 0; i < numAtoms; i++) if (atomMolecule[i] == -1) tagAtomsInMolecule(i, numMolecules++, atomMolecule, atomBonds); vector > atomIndices(numMolecules); for (int i = 0; i < numAtoms; i++) atomIndices[atomMolecule[i]].push_back(i); // Construct a description of each molecule. vector molecules(numMolecules); for (int i = 0; i < numMolecules; i++) { molecules[i].atoms = atomIndices[i]; molecules[i].groups.resize(forces.size()); } for (int i = 0; i < system.getNumConstraints(); i++) { int particle1, particle2; double distance; system.getConstraintParameters(i, particle1, particle2, distance); molecules[atomMolecule[particle1]].constraints.push_back(i); } for (int i = 0; i < (int) forces.size(); i++) for (int j = 0; j < forces[i]->getNumParticleGroups(); j++) { vector particles; forces[i]->getParticlesInGroup(j, particles); molecules[atomMolecule[particles[0]]].groups[i].push_back(j); } // Sort them into groups of identical molecules. vector uniqueMolecules; vector > moleculeInstances; for (int molIndex = 0; molIndex < (int) molecules.size(); molIndex++) { Molecule& mol = molecules[molIndex]; // See if it is identical to another molecule. bool isNew = true; for (int j = 0; j < (int) uniqueMolecules.size() && isNew; j++) { Molecule& mol2 = uniqueMolecules[j]; bool identical = (mol.atoms.size() == mol2.atoms.size() && mol.constraints.size() == mol2.constraints.size()); // See if the atoms are identical. int atomOffset = mol2.atoms[0]-mol.atoms[0]; for (int i = 0; i < (int) mol.atoms.size() && identical; i++) { if (mol.atoms[i] != mol2.atoms[i]-atomOffset || system.getParticleMass(mol.atoms[i]) != system.getParticleMass(mol2.atoms[i])) identical = false; for (int k = 0; k < (int) forces.size(); k++) if (!forces[k]->areParticlesIdentical(mol.atoms[i], mol2.atoms[i])) identical = false; } // See if the constraints are identical. for (int i = 0; i < (int) mol.constraints.size() && identical; i++) { int c1particle1, c1particle2, c2particle1, c2particle2; double distance1, distance2; system.getConstraintParameters(mol.constraints[i], c1particle1, c1particle2, distance1); system.getConstraintParameters(mol2.constraints[i], c2particle1, c2particle2, distance2); if (c1particle1 != c2particle1-atomOffset || c1particle2 != c2particle2-atomOffset || distance1 != distance2) identical = false; } // See if the force groups are identical. for (int i = 0; i < (int) forces.size() && identical; i++) { if (mol.groups[i].size() != mol2.groups[i].size()) identical = false; for (int k = 0; k < (int) mol.groups[i].size() && identical; k++) if (!forces[i]->areGroupsIdentical(mol.groups[i][k], mol2.groups[i][k])) identical = false; } if (identical) { moleculeInstances[j].push_back(mol.atoms[0]); isNew = false; } } if (isNew) { uniqueMolecules.push_back(mol); moleculeInstances.push_back(vector()); moleculeInstances[moleculeInstances.size()-1].push_back(mol.atoms[0]); } } moleculeGroups.resize(moleculeInstances.size()); for (int i = 0; i < (int) moleculeInstances.size(); i++) { moleculeGroups[i].instances = moleculeInstances[i]; vector& atoms = uniqueMolecules[i].atoms; moleculeGroups[i].atoms.resize(atoms.size()); for (int j = 0; j < (int) atoms.size(); j++) moleculeGroups[i].atoms[j] = atoms[j]-atoms[0]; } } void OpenCLContext::reorderAtoms() { if (numAtoms == 0 || nonbonded == NULL || !nonbonded->getUseCutoff()) return; atomsWereReordered = true; // Find the range of positions and the number of bins along each axis. posq->download(); velm->download(); float minx = posq->get(0).x, maxx = posq->get(0).x; float miny = posq->get(0).y, maxy = posq->get(0).y; float minz = posq->get(0).z, maxz = posq->get(0).z; if (nonbonded->getUsePeriodic()) { minx = miny = minz = 0.0; maxx = periodicBoxSize.x; maxy = periodicBoxSize.y; maxz = periodicBoxSize.z; } else { for (int i = 1; i < numAtoms; i++) { const mm_float4& pos = posq->get(i); minx = min(minx, pos.x); maxx = max(maxx, pos.x); miny = min(miny, pos.y); maxy = max(maxy, pos.y); minz = min(minz, pos.z); maxz = max(maxz, pos.z); } } // Loop over each group of identical molecules and reorder them. vector originalIndex(numAtoms); vector newPosq(numAtoms); vector newVelm(numAtoms); vector newCellOffsets(numAtoms); for (int group = 0; group < (int) moleculeGroups.size(); group++) { // Find the center of each molecule. MoleculeGroup& mol = moleculeGroups[group]; int numMolecules = mol.instances.size(); vector& atoms = mol.atoms; vector molPos(numMolecules); float invNumAtoms = 1.0f/atoms.size(); for (int i = 0; i < numMolecules; i++) { molPos[i].x = 0.0f; molPos[i].y = 0.0f; molPos[i].z = 0.0f; for (int j = 0; j < (int)atoms.size(); j++) { int atom = atoms[j]+mol.instances[i]; const mm_float4& pos = posq->get(atom); molPos[i].x += pos.x; molPos[i].y += pos.y; molPos[i].z += pos.z; } molPos[i].x *= invNumAtoms; molPos[i].y *= invNumAtoms; molPos[i].z *= invNumAtoms; } if (nonbonded->getUsePeriodic()) { // Move each molecule position into the same box. for (int i = 0; i < numMolecules; i++) { int xcell = (int) floor(molPos[i].x*invPeriodicBoxSize.x); int ycell = (int) floor(molPos[i].y*invPeriodicBoxSize.y); int zcell = (int) floor(molPos[i].z*invPeriodicBoxSize.z); float dx = xcell*periodicBoxSize.x; float dy = ycell*periodicBoxSize.y; float dz = zcell*periodicBoxSize.z; if (dx != 0.0f || dy != 0.0f || dz != 0.0f) { molPos[i].x -= dx; molPos[i].y -= dy; molPos[i].z -= dz; for (int j = 0; j < (int) atoms.size(); j++) { int atom = atoms[j]+mol.instances[i]; mm_float4 p = posq->get(atom); p.x -= dx; p.y -= dy; p.z -= dz; posq->set(atom, p); posCellOffsets[atom].x -= xcell; posCellOffsets[atom].y -= ycell; posCellOffsets[atom].z -= zcell; } } } } // Select a bin for each molecule, then sort them by bin. bool useHilbert = (numMolecules > 5000 || atoms.size() > 8); // For small systems, a simple zigzag curve works better than a Hilbert curve. float binWidth; if (useHilbert) binWidth = (float)(max(max(maxx-minx, maxy-miny), maxz-minz)/255.0); else binWidth = (float)(0.2*nonbonded->getCutoffDistance()); float invBinWidth = 1.0f/binWidth; int xbins = 1 + (int) ((maxx-minx)*invBinWidth); int ybins = 1 + (int) ((maxy-miny)*invBinWidth); vector > molBins(numMolecules); bitmask_t coords[3]; for (int i = 0; i < numMolecules; i++) { int x = (int) ((molPos[i].x-minx)*invBinWidth); int y = (int) ((molPos[i].y-miny)*invBinWidth); int z = (int) ((molPos[i].z-minz)*invBinWidth); int bin; if (useHilbert) { coords[0] = x; coords[1] = y; coords[2] = z; bin = (int) hilbert_c2i(3, 8, coords); } else { int yodd = y&1; int zodd = z&1; bin = z*xbins*ybins; bin += (zodd ? ybins-y : y)*xbins; bin += (yodd ? xbins-x : x); } molBins[i] = pair(bin, i); } sort(molBins.begin(), molBins.end()); // Reorder the atoms. for (int i = 0; i < numMolecules; i++) { for (int j = 0; j < (int)atoms.size(); j++) { int oldIndex = mol.instances[molBins[i].second]+atoms[j]; int newIndex = mol.instances[i]+atoms[j]; originalIndex[newIndex] = atomIndex->get(oldIndex); newPosq[newIndex] = posq->get(oldIndex); newVelm[newIndex] = velm->get(oldIndex); newCellOffsets[newIndex] = posCellOffsets[oldIndex]; } } } // Update the streams. for (int i = 0; i < numAtoms; i++) { posq->set(i, newPosq[i]); velm->set(i, newVelm[i]); atomIndex->set(i, originalIndex[i]); posCellOffsets[i] = newCellOffsets[i]; } posq->upload(); velm->upload(); atomIndex->upload(); for (int i = 0; i < (int) reorderListeners.size(); i++) reorderListeners[i]->execute(); } void OpenCLContext::addReorderListener(ReorderListener* listener) { reorderListeners.push_back(listener); } struct OpenCLContext::WorkThread::ThreadData { ThreadData(std::queue& tasks, bool& waiting, bool& finished, pthread_mutex_t& queueLock, pthread_cond_t& waitForTaskCondition, pthread_cond_t& queueEmptyCondition) : tasks(tasks), waiting(waiting), finished(finished), queueLock(queueLock), waitForTaskCondition(waitForTaskCondition), queueEmptyCondition(queueEmptyCondition) { } std::queue& tasks; bool& waiting; bool& finished; pthread_mutex_t& queueLock; pthread_cond_t& waitForTaskCondition; pthread_cond_t& queueEmptyCondition; }; static void* threadBody(void* args) { OpenCLContext::WorkThread::ThreadData& data = *reinterpret_cast(args); while (!data.finished || data.tasks.size() > 0) { pthread_mutex_lock(&data.queueLock); while (data.tasks.empty() && !data.finished) { data.waiting = true; pthread_cond_signal(&data.queueEmptyCondition); pthread_cond_wait(&data.waitForTaskCondition, &data.queueLock); } OpenCLContext::WorkTask* task = NULL; if (!data.tasks.empty()) { data.waiting = false; task = data.tasks.front(); data.tasks.pop(); } pthread_mutex_unlock(&data.queueLock); if (task != NULL) { task->execute(); delete task; } } data.waiting = true; pthread_cond_signal(&data.queueEmptyCondition); delete &data; return 0; } OpenCLContext::WorkThread::WorkThread() : waiting(true), finished(false) { pthread_mutex_init(&queueLock, NULL); pthread_cond_init(&waitForTaskCondition, NULL); pthread_cond_init(&queueEmptyCondition, NULL); ThreadData* data = new ThreadData(tasks, waiting, finished, queueLock, waitForTaskCondition, queueEmptyCondition); pthread_create(&thread, NULL, threadBody, data); } OpenCLContext::WorkThread::~WorkThread() { pthread_mutex_lock(&queueLock); finished = true; pthread_cond_broadcast(&waitForTaskCondition); pthread_mutex_unlock(&queueLock); pthread_join(thread, NULL); pthread_mutex_destroy(&queueLock); pthread_cond_destroy(&waitForTaskCondition); pthread_cond_destroy(&queueEmptyCondition); } void OpenCLContext::WorkThread::addTask(OpenCLContext::WorkTask* task) { pthread_mutex_lock(&queueLock); tasks.push(task); waiting = false; pthread_cond_signal(&waitForTaskCondition); pthread_mutex_unlock(&queueLock); } bool OpenCLContext::WorkThread::isWaiting() { return waiting; } bool OpenCLContext::WorkThread::isFinished() { return finished; } void OpenCLContext::WorkThread::flush() { pthread_mutex_lock(&queueLock); while (!waiting) pthread_cond_wait(&queueEmptyCondition, &queueLock); pthread_mutex_unlock(&queueLock); }