// ================================================================================================= // 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 Xgemv class (see the header for information about the class). // // ================================================================================================= #include "routines/level2/xgemv.hpp" #include #include namespace clblast { // ================================================================================================= // Constructor: forwards to base class constructor template Xgemv::Xgemv(Queue &queue, EventPointer event, const std::string &name): Routine(queue, event, name, {"Pad", "Xgemv", "XgemvFast", "XgemvFastRot"}, PrecisionValue(), {}, { #include "../../kernels/level2/xgemv.opencl" #include "../../kernels/level2/xgemv_fast.opencl" }) { } // ================================================================================================= // The main routine template void Xgemv::DoGemv(const Layout layout, const Transpose a_transpose, const size_t m, const size_t n, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, const Buffer &x_buffer, const size_t x_offset, const size_t x_inc, const T beta, const Buffer &y_buffer, const size_t y_offset, const size_t y_inc) { // Performs the matrix-vector multiplication MatVec(layout, a_transpose, m, n, alpha, a_buffer, a_offset, a_ld, x_buffer, x_offset, x_inc, beta, y_buffer, y_offset, y_inc, true, true, 0, false, 0, 0); // N/A for this routine } // ================================================================================================= // The generic implementation, also suited for other (non general) matrix-vector multiplications template void Xgemv::MatVec(const Layout layout, const Transpose a_transpose, const size_t m, const size_t n, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, const Buffer &x_buffer, const size_t x_offset, const size_t x_inc, const T beta, const Buffer &y_buffer, const size_t y_offset, const size_t y_inc, bool fast_kernel, bool fast_kernel_rot, const size_t parameter, const bool packed, const size_t kl, const size_t ku) { // Makes sure all dimensions are larger than zero if (m == 0 || n == 0) { throw BLASError(StatusCode::kInvalidDimension); } // Computes whether or not the matrix has an alternative layout (row or column-major). auto a_altlayout = (layout == Layout::kRowMajor); auto a_one = (a_altlayout) ? n : m; auto a_two = (a_altlayout) ? m : n; // Swap m and n if the matrix is transposed auto a_transposed = (a_transpose != Transpose::kNo); auto m_real = (a_transposed) ? n : m; auto n_real = (a_transposed) ? m : n; // Special adjustments for banded matrices if (kl != 0 || ku != 0) { a_one = kl+ku+1; } // Determines whether the kernel needs to perform rotated access ('^' is the XOR operator) auto a_rotated = a_transposed ^ a_altlayout; // In case of complex data-types, the transpose can also become a conjugate transpose auto a_conjugate = (a_transpose == Transpose::kConjugate); // Tests the matrix and the vectors for validity if (packed) { TestMatrixAP(n, a_buffer, a_offset); } else { TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); } TestVectorX(n_real, x_buffer, x_offset, x_inc); TestVectorY(m_real, y_buffer, y_offset, y_inc); // Determines whether or not the fast-version can be used fast_kernel = fast_kernel && (a_offset == 0) && (a_rotated == 0) && (a_conjugate == 0) && IsMultiple(m, db_["WGS2"]*db_["WPT2"]) && IsMultiple(n, db_["WGS2"]) && IsMultiple(a_ld, db_["VW2"]); fast_kernel_rot = fast_kernel_rot && (a_offset == 0) && (a_rotated == 1) && (a_conjugate == 0) && IsMultiple(m, db_["WGS3"]*db_["WPT3"]) && IsMultiple(n, db_["WGS3"]) && IsMultiple(a_ld, db_["VW3"]); // If possible, run the fast-version (rotated or non-rotated) of the kernel auto kernel_name = "Xgemv"; auto m_ceiled = Ceil(m_real, db_["WGS1"]*db_["WPT1"]); auto global_size = m_ceiled / db_["WPT1"]; auto local_size = db_["WGS1"]; if (fast_kernel) { kernel_name = "XgemvFast"; global_size = m_real / db_["WPT2"]; local_size = db_["WGS2"]; } if (fast_kernel_rot) { kernel_name = "XgemvFastRot"; global_size = m_real; local_size = db_["WGS3"]; } // Retrieves the Xgemv kernel from the compiled binary const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); auto kernel = Kernel(program, kernel_name); // Sets the kernel arguments kernel.SetArgument(0, static_cast(m_real)); kernel.SetArgument(1, static_cast(n_real)); kernel.SetArgument(2, GetRealArg(alpha)); kernel.SetArgument(3, GetRealArg(beta)); kernel.SetArgument(4, static_cast(a_rotated)); kernel.SetArgument(5, a_buffer()); kernel.SetArgument(6, static_cast(a_offset)); kernel.SetArgument(7, static_cast(a_ld)); kernel.SetArgument(8, x_buffer()); kernel.SetArgument(9, static_cast(x_offset)); kernel.SetArgument(10, static_cast(x_inc)); kernel.SetArgument(11, y_buffer()); kernel.SetArgument(12, static_cast(y_offset)); kernel.SetArgument(13, static_cast(y_inc)); kernel.SetArgument(14, static_cast(a_conjugate)); kernel.SetArgument(15, static_cast(parameter)); // extra parameter used for symm/herm kernel.SetArgument(16, static_cast(kl)); // only used for banded matrices kernel.SetArgument(17, static_cast(ku)); // only used for banded matrices // Launches the kernel auto global = std::vector{global_size}; auto local = std::vector{local_size}; RunKernel(kernel, queue_, device_, global, local, event_); } // ================================================================================================= // Compiles the templated class template class Xgemv; template class Xgemv; template class Xgemv; template class Xgemv; template class Xgemv; // ================================================================================================= } // namespace clblast