// ================================================================================================= // 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 implements the Xsyrk class (see the header for information about the class). // // ================================================================================================= #include "routines/level3/xsyrk.hpp" #include #include namespace clblast { // ================================================================================================= // Constructor: forwards to base class constructor template Xsyrk::Xsyrk(Queue &queue, EventPointer event, const std::string &name): Routine(queue, event, name, {"Copy","Pad","Transpose","Padtranspose","Xgemm"}, PrecisionValue()) { source_string_ = #include "../../kernels/level3/level3.opencl" #include "../../kernels/level3/copy_fast.opencl" #include "../../kernels/level3/copy_pad.opencl" #include "../../kernels/level3/transpose_fast.opencl" #include "../../kernels/level3/transpose_pad.opencl" #include "../../kernels/level3/xgemm_part1.opencl" #include "../../kernels/level3/xgemm_part2.opencl" #include "../../kernels/level3/xgemm_part3.opencl" ; } // ================================================================================================= // The main routine template StatusCode Xsyrk::DoSyrk(const Layout layout, const Triangle triangle, const Transpose a_transpose, const size_t n, const size_t k, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, const T beta, const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero if ((n == 0) || (k == 0) ) { return StatusCode::kInvalidDimension; } // Computes whether or not the matrices are transposed in memory. This is based on their layout // (row or column-major) and whether or not they are requested to be pre-transposed. auto a_rotated = (layout == Layout::kColMajor && a_transpose != Transpose::kNo) || (layout == Layout::kRowMajor && a_transpose == Transpose::kNo); auto c_rotated = (layout == Layout::kRowMajor); // Computes the first and second dimensions of the A matrix taking the layout into account auto a_one = (a_rotated) ? k : n; auto a_two = (a_rotated) ? n : k; // Tests the two matrices (A, C) for validity, first from a perspective of the OpenCL buffers and // their sizes, and then from a perspective of parameter values (e.g. n, k). Tests whether the // OpenCL buffers are valid and non-zero and whether the OpenCL buffers have sufficient storage // space. Also tests that the leading dimensions of: // matrix A cannot be less than N when rotated, or less than K when not-rotated // matrix C cannot be less than N auto status = TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); if (ErrorIn(status)) { return status; } status = TestMatrixC(n, n, c_buffer, c_offset, c_ld); if (ErrorIn(status)) { return status; } // Calculates the ceiled versions of n and k auto n_ceiled = Ceil(Ceil(n, db_["MWG"]), db_["NWG"]); auto k_ceiled = Ceil(k, db_["KWG"]); // Decides which kernel to run: the upper-triangular or lower-triangular version auto kernel_name = (triangle == Triangle::kUpper) ? "XgemmUpper" : "XgemmLower"; // The padded/transposed input/output matrices: if memory allocation fails, throw an exception try { // Loads the program from the database const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); // Determines whether or not temporary matrices are needed auto a_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && a_rotated == false; // Creates the temporary matrices auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); auto c_temp = Buffer(context_, n_ceiled*n_ceiled); // Events of all kernels (including pre/post processing kernels) auto eventWaitList = std::vector(); auto emptyEventList = std::vector(); // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In // case nothing has to be done, these kernels can be skipped. if (!a_no_temp) { auto eventProcessA = Event(); status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, a_one, a_two, a_ld, a_offset, a_buffer, n_ceiled, k_ceiled, n_ceiled, 0, a_temp, ConstantOne(), program, true, a_rotated, false); if (ErrorIn(status)) { return status; } eventWaitList.push_back(eventProcessA); } // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to // modify the other triangle. auto eventProcessC = Event(); status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, n, n, c_ld, c_offset, c_buffer, n_ceiled, n_ceiled, n_ceiled, 0, c_temp, ConstantOne(), program, true, c_rotated, false); if (ErrorIn(status)) { return status; } eventWaitList.push_back(eventProcessC); // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary try { auto kernel = Kernel(program, kernel_name); // Sets the kernel arguments kernel.SetArgument(0, static_cast(n_ceiled)); kernel.SetArgument(1, static_cast(k_ceiled)); kernel.SetArgument(2, GetRealArg(alpha)); kernel.SetArgument(3, GetRealArg(beta)); kernel.SetArgument(4, a_temp()); kernel.SetArgument(5, a_temp()); kernel.SetArgument(6, c_temp()); // Computes the global and local thread sizes auto global = std::vector{ (n_ceiled * db_["MDIMC"]) / db_["MWG"], (n_ceiled * db_["NDIMC"]) / db_["NWG"] }; auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; // Launches the kernel auto eventKernel = Event(); status = RunKernel(kernel, queue_, device_, global, local, eventKernel.pointer(), eventWaitList); if (ErrorIn(status)) { return status; } eventWaitList.push_back(eventKernel); // Runs the post-processing kernel auto upper = (triangle == Triangle::kUpper); auto lower = (triangle == Triangle::kLower); status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, n_ceiled, n_ceiled, n_ceiled, 0, c_temp, n, n, c_ld, c_offset, c_buffer, ConstantOne(), program, false, c_rotated, false, upper, lower, false); if (ErrorIn(status)) { return status; } // Successfully finished the computation return StatusCode::kSuccess; } catch (...) { return StatusCode::kInvalidKernel; } } catch (...) { return StatusCode::kTempBufferAllocFailure; } } // ================================================================================================= // Compiles the templated class template class Xsyrk; template class Xsyrk; template class Xsyrk; template class Xsyrk; template class Xsyrk; // ================================================================================================= } // namespace clblast