// ================================================================================================= // This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This // project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max- // width of 100 characters per line. // // Author(s): // Cedric Nugteren // // This file uses the auto-tuner to tune the xgemm OpenCL kernels. There are two variations: // - V==1: This tests some limited set of tuning parameters exhaustively. // - V==2: This tests a much larger set of tuning parameters by randomly sampling a subset. // // ================================================================================================= #include #include #include "utilities/utilities.hpp" #include "tuning/tuning.hpp" namespace clblast { // ================================================================================================= // Settings for this kernel (default command-line arguments) TunerDefaults GetTunerDefaults(const int V) { auto settings = TunerDefaults(); settings.options = {kArgM, kArgN, kArgK, kArgAlpha, kArgBeta, kArgFraction, kArgHeuristicSelection, kArgPsoSwarmSize, kArgPsoInfGlobal, kArgPsoInfLocal, kArgPsoInfRandom}; settings.default_m = 1024; settings.default_n = 1024; settings.default_k = 1024; settings.default_fraction = (V==1) ? 1.0 : 512.0; // test all or sample randomly settings.default_num_runs = 2; return settings; } // Settings for this kernel (general) template TunerSettings GetTunerSettings(const int V, const Arguments &args) { auto settings = TunerSettings(); // Identification of the kernel settings.kernel_family = (V==1) ? "xgemm_1" : "xgemm_2"; settings.kernel_name = "Xgemm"; settings.sources = #include "../src/kernels/level3/xgemm_part1.opencl" #include "../src/kernels/level3/xgemm_part2.opencl" #include "../src/kernels/level3/xgemm_part3.opencl" #include "../src/kernels/level3/xgemm_part4.opencl" ; // Buffer sizes settings.size_a = args.m * args.k; settings.size_b = args.n * args.k; settings.size_c = args.m * args.n; // Inputs and outputs IDs (X:0, Y:1, A:2, B:3, C:4, temp:5) settings.inputs = {2, 3, 4}; settings.outputs = {4}; // Sets the base thread configuration settings.global_size = {args.m, args.n}; settings.global_size_ref = settings.global_size; settings.local_size = {1, 1}; settings.local_size_ref = {8, 8}; // Transforms the thread configuration based on the parameters settings.mul_local = {{"MDIMC", "NDIMC"}}; settings.mul_global = {{"MDIMC", "NDIMC"}}; settings.div_global = {{"MWG", "NWG"}}; // Sets the tuning parameters and their possible values if (V==1) { // limited subset of tuning parameters - but explorable exhaustively settings.parameters = { {"MWG", {16, 32, 64}}, {"NWG", {16, 32, 64}}, {"KWG", {32}}, {"MDIMC", {8, 16, 32}}, {"NDIMC", {8, 16, 32}}, {"MDIMA", {8, 16, 32}}, {"NDIMB", {8, 16, 32}}, {"KWI", {2}}, {"VWM", {1, 2, 4}}, {"VWN", {1, 2, 4}}, {"STRM", {0}}, {"STRN", {0}}, {"SA", {0, 1}}, {"SB", {0, 1}}, }; } else { // a lot more tuning parameters - has to be sampled randomly, too much to test all settings.parameters = { {"MWG", {16, 32, 64, 128}}, {"NWG", {16, 32, 64, 128}}, {"KWG", {16, 32}}, {"MDIMC", {8, 16, 32}}, {"NDIMC", {8, 16, 32}}, {"MDIMA", {8, 16, 32}}, {"NDIMB", {8, 16, 32}}, {"KWI", {2}}, {"VWM", {1, 2, 4, 8}}, {"VWN", {1, 2, 4, 8}}, {"STRM", {0, 1}}, {"STRN", {0, 1}}, {"SA", {0, 1}}, {"SB", {0, 1}}, }; } // Describes how to compute the performance metrics settings.metric_amount = 2 * args.m * args.n * args.k; settings.performance_unit = "GFLOPS"; return settings; } // Tests for valid arguments template void TestValidArguments(const int, const Arguments &) { } std::vector SetConstraints(const int V) { auto constraints = std::vector(); auto MultipleOfX = [] (std::vector v) { return IsMultiple(v[0], v[1]); }; auto MultipleOfXMulY = [] (std::vector v) { return IsMultiple(v[0], v[1]*v[2]); }; auto MultipleOfXMulYDivZ = [] (std::vector v) { return IsMultiple(v[0], (v[1]*v[2])/v[3]); }; // Requirement for unrolling the KWG loop constraints.push_back({MultipleOfX, {"KWG", "KWI"}}); // Required for integer MWI and NWI constraints.push_back({MultipleOfXMulY, {"MWG", "MDIMC", "VWM"}}); constraints.push_back({MultipleOfXMulY, {"NWG", "NDIMC", "VWN"}}); // Required for integer MWIA and NWIB constraints.push_back({MultipleOfXMulY, {"MWG", "MDIMA", "VWM"}}); constraints.push_back({MultipleOfXMulY, {"NWG", "NDIMB", "VWN"}}); // KWG has to be a multiple of KDIMA = ((MDIMC*NDIMC)/(MDIMA)) and KDIMB = (...) constraints.push_back({MultipleOfXMulYDivZ, {"KWG", "MDIMC", "NDIMC", "MDIMA"}}); constraints.push_back({MultipleOfXMulYDivZ, {"KWG", "MDIMC", "NDIMC", "NDIMB"}}); // Extra constraints for variation 1 to limit the set of options significantly if (V==1) { auto IsEqual = [] (std::vector v) { return v[0] == v[1]; }; constraints.push_back({IsEqual, {"MDIMC", "MDIMA"}}); constraints.push_back({IsEqual, {"NDIMC", "NDIMB"}}); constraints.push_back({IsEqual, {"SA", "SB"}}); } return constraints; } // Sets the kernel's arguments template void SetArguments(const int, Kernel &kernel, const Arguments &args, std::vector>& buffers) { kernel.SetArgument(0, static_cast(args.m)); kernel.SetArgument(1, static_cast(args.n)); kernel.SetArgument(2, static_cast(args.k)); kernel.SetArgument(3, GetRealArg(args.alpha)); kernel.SetArgument(4, GetRealArg(args.beta)); kernel.SetArgument(5, buffers[2]()); // 2 == A matrix kernel.SetArgument(6, buffers[3]()); // 3 == B matrix kernel.SetArgument(7, buffers[4]()); // 4 == C matrix kernel.SetArgument(8, 0); kernel.SetArgument(9, 0); } // ================================================================================================= } // namespace clblast