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// =================================================================================================
// 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 Xher2k class (see the header for information about the class).
//
// =================================================================================================
#include "internal/routines/level3/xher2k.h"
#include <string>
#include <vector>
namespace clblast {
// =================================================================================================
// Specific implementations to get the memory-type based on a template argument
template <> const Precision Xher2k<float2,float>::precision_ = Precision::kComplexSingle;
template <> const Precision Xher2k<double2,double>::precision_ = Precision::kComplexDouble;
// =================================================================================================
// Constructor: forwards to base class constructor
template <typename T, typename U>
Xher2k<T,U>::Xher2k(CommandQueue &queue, Event &event):
Routine(queue, event, {"Copy", "Pad", "Transpose", "PadTranspose", "Xgemm"}, precision_) {
}
// =================================================================================================
// The main routine
template <typename T, typename U>
StatusCode Xher2k<T,U>::DoHer2k(const Layout layout, const Triangle triangle, const Transpose ab_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 Buffer &b_buffer, const size_t b_offset, const size_t b_ld,
const U 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; }
// Determines whether to apply the conjugate transpose to matrix B (argument: no transpose) or
// to matrix A (argument: conjugate transpose)
auto ab_conjugate = (ab_transpose != Transpose::kNo);
// 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 ab_rotated = (layout == Layout::kColMajor && ab_conjugate) ||
(layout == Layout::kRowMajor && !ab_conjugate);
auto c_rotated = (layout == Layout::kRowMajor);
// Computes the first and second dimensions of the A and B matrices taking the layout into account
auto ab_one = (ab_rotated) ? k : n;
auto ab_two = (ab_rotated) ? n : k;
// Tests the 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. 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 B cannot be less than N when rotated, or less than K when not-rotated
// matrix C cannot be less than N
auto status = TestMatrixA(ab_one, ab_two, a_buffer, a_offset, a_ld, sizeof(T));
if (ErrorIn(status)) { return status; }
status = TestMatrixB(ab_one, ab_two, b_buffer, b_offset, b_ld, sizeof(T));
if (ErrorIn(status)) { return status; }
status = TestMatrixC(n, n, c_buffer, c_offset, c_ld, sizeof(T));
if (ErrorIn(status)) { return status; }
// Calculates the ceiled versions of n and k
auto n_ceiled = Ceil(n, 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";
// Allocates space on the device for padded and/or transposed input and output matrices.
try {
auto temp_a1 = Buffer(context_, CL_MEM_READ_WRITE, k_ceiled*n_ceiled*sizeof(T));
auto temp_b1 = Buffer(context_, CL_MEM_READ_WRITE, k_ceiled*n_ceiled*sizeof(T));
auto temp_a2 = Buffer(context_, CL_MEM_READ_WRITE, k_ceiled*n_ceiled*sizeof(T));
auto temp_b2 = Buffer(context_, CL_MEM_READ_WRITE, k_ceiled*n_ceiled*sizeof(T));
auto temp_c = Buffer(context_, CL_MEM_READ_WRITE, n_ceiled*n_ceiled*sizeof(T));
// Loads the program from the database
auto& program = GetProgramFromCache();
// Runs the pre-processing kernels. This transposes the matrices A and B, but also pads zeros to
// fill them up until they reach a certain multiple of size (kernel parameter dependent).
status = PadCopyTransposeMatrix(ab_one, ab_two, a_ld, a_offset, a_buffer,
n_ceiled, k_ceiled, n_ceiled, 0, temp_a1,
program, true, ab_rotated, ab_conjugate);
if (ErrorIn(status)) { return status; }
status = PadCopyTransposeMatrix(ab_one, ab_two, a_ld, a_offset, a_buffer,
n_ceiled, k_ceiled, n_ceiled, 0, temp_a2,
program, true, ab_rotated, !ab_conjugate);
if (ErrorIn(status)) { return status; }
status = PadCopyTransposeMatrix(ab_one, ab_two, b_ld, b_offset, b_buffer,
n_ceiled, k_ceiled, n_ceiled, 0, temp_b1,
program, true, ab_rotated, ab_conjugate);
status = PadCopyTransposeMatrix(ab_one, ab_two, b_ld, b_offset, b_buffer,
n_ceiled, k_ceiled, n_ceiled, 0, temp_b2,
program, true, ab_rotated, !ab_conjugate);
if (ErrorIn(status)) { return status; }
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
// modify the other triangle.
status = PadCopyTransposeMatrix(n, n, c_ld, c_offset, c_buffer,
n_ceiled, n_ceiled, n_ceiled, 0, temp_c,
program, true, c_rotated, false);
if (ErrorIn(status)) { return status; }
// Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary
try {
auto kernel = Kernel(program, kernel_name);
// Sets the kernel arguments
auto complex_beta = T{beta, static_cast<U>(0.0)};
kernel.SetArgument(0, static_cast<int>(n_ceiled));
kernel.SetArgument(1, static_cast<int>(k_ceiled));
kernel.SetArgument(2, alpha);
kernel.SetArgument(3, complex_beta);
kernel.SetArgument(4, temp_a1());
kernel.SetArgument(5, temp_b2());
kernel.SetArgument(6, temp_c());
// Computes the global and local thread sizes
auto global = std::vector<size_t>{
(n_ceiled * db_["MDIMC"]) / db_["MWG"],
(n_ceiled * db_["NDIMC"]) / db_["NWG"]
};
auto local = std::vector<size_t>{db_["MDIMC"], db_["NDIMC"]};
// Launches the kernel
status = RunKernel(kernel, global, local);
if (ErrorIn(status)) { return status; }
// Swaps the arguments for matrices A and B, sets 'beta' to 1, and conjugate alpha
auto conjugate_alpha = T{alpha.real(), -alpha.imag()};
auto complex_one = T{static_cast<U>(1.0), static_cast<U>(0.0)};
kernel.SetArgument(2, conjugate_alpha);
kernel.SetArgument(3, complex_one);
kernel.SetArgument(4, temp_b1());
kernel.SetArgument(5, temp_a2());
// Runs the kernel again
status = RunKernel(kernel, global, local);
if (ErrorIn(status)) { return status; }
// Runs the post-processing kernel
auto upper = (triangle == Triangle::kUpper);
auto lower = (triangle == Triangle::kLower);
status = PadCopyTransposeMatrix(n_ceiled, n_ceiled, n_ceiled, 0, temp_c,
n, n, c_ld, c_offset, c_buffer,
program, false, c_rotated, false, upper, lower, true);
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 Xher2k<float2,float>;
template class Xher2k<double2,double>;
// =================================================================================================
} // namespace clblast
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