diff options
Diffstat (limited to 'src/routines/level3/xgemm.cpp')
| -rw-r--r-- | src/routines/level3/xgemm.cpp | 223 |
1 files changed, 223 insertions, 0 deletions
diff --git a/src/routines/level3/xgemm.cpp b/src/routines/level3/xgemm.cpp new file mode 100644 index 00000000..9ea5559c --- /dev/null +++ b/src/routines/level3/xgemm.cpp @@ -0,0 +1,223 @@ + +// ================================================================================================= +// 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 <www.cedricnugteren.nl> +// +// This file implements the Xgemm class (see the header for information about the class). +// +// ================================================================================================= + +#include "routines/level3/xgemm.hpp" + +#include <string> +#include <vector> + +namespace clblast { +// ================================================================================================= + +// Constructor: forwards to base class constructor +template <typename T> +Xgemm<T>::Xgemm(Queue &queue, EventPointer event, const std::string &name): + Routine(queue, event, name, {"Copy","Pad","Transpose","Padtranspose","Xgemm"}, PrecisionValue<T>()) { + 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/convert_symmetric.opencl" + #include "../../kernels/level3/convert_triangular.opencl" + #include "../../kernels/level3/convert_hermitian.opencl" + #include "../../kernels/level3/xgemm_part1.opencl" + #include "../../kernels/level3/xgemm_part2.opencl" + ; +} + +// ================================================================================================= + +// The main routine +template <typename T> +StatusCode Xgemm<T>::DoGemm(const Layout layout, + const Transpose a_transpose, const Transpose b_transpose, + const size_t m, const size_t n, const size_t k, + const T alpha, + const Buffer<T> &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer<T> &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer<T> &c_buffer, const size_t c_offset, const size_t c_ld) { + + // Makes sure all dimensions are larger than zero + if ((m == 0) || (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. Note + // that the Xgemm kernel expects either matrices A and C (in case of row-major) or B (in case of + // col-major) to be transformed, so transposing requirements are not the same as whether or not + // the matrix is actually transposed in memory. + const auto a_rotated = (layout == Layout::kColMajor && a_transpose != Transpose::kNo) || + (layout == Layout::kRowMajor && a_transpose == Transpose::kNo); + const auto b_rotated = (layout == Layout::kColMajor && b_transpose != Transpose::kNo) || + (layout == Layout::kRowMajor && b_transpose == Transpose::kNo); + const auto c_rotated = (layout == Layout::kRowMajor); + const auto a_do_transpose = a_rotated; + const auto b_do_transpose = !b_rotated; + const auto c_do_transpose = c_rotated; + + // In case of complex data-types, the transpose can also become a conjugate transpose + const auto a_conjugate = (a_transpose == Transpose::kConjugate); + const auto b_conjugate = (b_transpose == Transpose::kConjugate); + + // Computes the first and second dimensions of the 3 matrices taking into account whether the + // matrices are rotated or not + const auto a_one = (a_rotated) ? k : m; + const auto a_two = (a_rotated) ? m : k; + const auto b_one = (b_rotated) ? n : k; + const auto b_two = (b_rotated) ? k : n; + const auto c_one = (c_rotated) ? n : m; + const auto c_two = (c_rotated) ? m : n; + + // Tests three matrices (A, B, C) for validity, first from a perspective of the OpenCL buffers and + // their sizes, and then from a perspective of parameter values (e.g. m, 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 K when rotated, or less than M when not-rotated + // matrix B cannot be less than N when rotated, or less than K when not-rotated + // matrix C cannot be less than N when rotated, or less than M when not-rotated + auto status = TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); + if (ErrorIn(status)) { return status; } + status = TestMatrixB(b_one, b_two, b_buffer, b_offset, b_ld); + if (ErrorIn(status)) { return status; } + status = TestMatrixC(c_one, c_two, c_buffer, c_offset, c_ld); + if (ErrorIn(status)) { return status; } + + // Calculates the ceiled versions of m, n, and k + const auto m_ceiled = Ceil(m, db_["MWG"]); + const auto n_ceiled = Ceil(n, db_["NWG"]); + const auto k_ceiled = Ceil(k, db_["KWG"]); + + // 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<T>(), routine_name_); + + // Determines whether or not temporary matrices are needed + auto a_no_temp = a_one == m_ceiled && a_two == k_ceiled && a_ld == m_ceiled && a_offset == 0 && + a_do_transpose == false && a_conjugate == false; + auto b_no_temp = b_one == n_ceiled && b_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && + b_do_transpose == false && b_conjugate == false; + auto c_no_temp = c_one == m_ceiled && c_two == n_ceiled && c_ld == m_ceiled && c_offset == 0 && + c_do_transpose == false; + + // Creates the temporary matrices + const auto a_temp = (a_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*m_ceiled); + const auto b_temp = (b_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled); + const auto c_temp = (c_no_temp) ? c_buffer : Buffer<T>(context_, m_ceiled*n_ceiled); + + // Upload the scalar arguments as constant buffers to the device (needed for half-precision) + auto alpha_buffer = Buffer<T>(context_, 1); + auto beta_buffer = Buffer<T>(context_, 1); + alpha_buffer.Write(queue_, 1, &alpha); + beta_buffer.Write(queue_, 1, &beta); + + // Events of all kernels (including pre/post processing kernels) + auto eventWaitList = std::vector<Event>(); + auto emptyEventList = std::vector<Event>(); + + // 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_, context_, db_, eventProcessA.pointer(), emptyEventList, + a_one, a_two, a_ld, a_offset, a_buffer, + m_ceiled, k_ceiled, m_ceiled, 0, a_temp, + ConstantOne<T>(), program, + true, a_do_transpose, a_conjugate); + if (ErrorIn(status)) { return status; } + eventWaitList.push_back(eventProcessA); + } + + // As above, but now for matrix B + if (!b_no_temp) { + auto eventProcessB = Event(); + status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessB.pointer(), emptyEventList, + b_one, b_two, b_ld, b_offset, b_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, b_temp, + ConstantOne<T>(), program, + true, b_do_transpose, b_conjugate); + if (ErrorIn(status)) { return status; } + eventWaitList.push_back(eventProcessB); + } + + // As above, but now for matrix C. This is only necessary if C is used both as input and output. + if (!c_no_temp && beta != static_cast<T>(0)) { + auto eventProcessC = Event(); + status = PadCopyTransposeMatrix(queue_, device_, context_, db_, eventProcessC.pointer(), emptyEventList, + c_one, c_two, c_ld, c_offset, c_buffer, + m_ceiled, n_ceiled, m_ceiled, 0, c_temp, + ConstantOne<T>(), program, + true, c_do_transpose, false); + if (ErrorIn(status)) { return status; } + eventWaitList.push_back(eventProcessC); + } + + // Retrieves the Xgemm kernel from the compiled binary + try { + auto kernel = Kernel(program, "Xgemm"); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast<int>(m_ceiled)); + kernel.SetArgument(1, static_cast<int>(n_ceiled)); + kernel.SetArgument(2, static_cast<int>(k_ceiled)); + kernel.SetArgument(3, alpha_buffer()); + kernel.SetArgument(4, beta_buffer()); + kernel.SetArgument(5, a_temp()); + kernel.SetArgument(6, b_temp()); + kernel.SetArgument(7, c_temp()); + + // Computes the global and local thread sizes + const auto global = std::vector<size_t>{ + (m_ceiled * db_["MDIMC"]) / db_["MWG"], + (n_ceiled * db_["NDIMC"]) / db_["NWG"] + }; + const auto local = std::vector<size_t>{db_["MDIMC"], db_["NDIMC"]}; + + // Launches the kernel + auto eventKernel = Event(); + auto eventPointer = (!c_no_temp) ? eventKernel.pointer() : event_; + status = RunKernel(kernel, queue_, device_, global, local, eventPointer, eventWaitList); + if (ErrorIn(status)) { return status; } + + // Runs the post-processing kernel if needed + if (!c_no_temp) { + eventWaitList.push_back(eventKernel); + status = PadCopyTransposeMatrix(queue_, device_, context_, db_, event_, eventWaitList, + m_ceiled, n_ceiled, m_ceiled, 0, c_temp, + c_one, c_two, c_ld, c_offset, c_buffer, + ConstantOne<T>(), program, + false, c_do_transpose, 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 Xgemm<half>; +template class Xgemm<float>; +template class Xgemm<double>; +template class Xgemm<float2>; +template class Xgemm<double2>; + +// ================================================================================================= +} // namespace clblast |