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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 Xsyr2k class (see the header for information about the class).
//
// =================================================================================================
#include "routines/level3/xsyr2k.hpp"
#include <string>
#include <vector>
namespace clblast {
// =================================================================================================
// Constructor: forwards to base class constructor
template <typename T>
Xsyr2k<T>::Xsyr2k(Queue &queue, EventPointer event, const std::string &name):
Routine(queue, event, name, {"Copy","Pad","Transpose","Padtranspose","Xgemm"}, PrecisionValue<T>(), {}, {
#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 <typename T>
void Xsyr2k<T>::DoSyr2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose,
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 ((n == 0) || (k == 0) ) { throw BLASError(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 ab_rotated = (layout == Layout::kColMajor && ab_transpose != Transpose::kNo) ||
(layout == Layout::kRowMajor && ab_transpose == Transpose::kNo);
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
TestMatrixA(ab_one, ab_two, a_buffer, a_offset, a_ld);
TestMatrixB(ab_one, ab_two, b_buffer, b_offset, b_ld);
TestMatrixC(n, n, c_buffer, c_offset, c_ld);
// 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";
// 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 = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 &&
ab_rotated == false;
auto b_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 &&
ab_rotated == false;
// Creates the temporary matrices
auto a_temp = (a_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
auto b_temp = (b_no_temp) ? b_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
// Events of all kernels (including pre/post processing kernels)
auto eventWaitList = std::vector<Event>();
auto emptyEventList = std::vector<Event>();
// Runs the pre-processing kernels. This transposes the matrices A and B, but also pads zeros to
// 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();
PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList,
ab_one, ab_two, a_ld, a_offset, a_buffer,
n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
ConstantOne<T>(), program,
true, ab_rotated, false);
eventWaitList.push_back(eventProcessA);
}
if (!b_no_temp) {
auto eventProcessB = Event();
PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList,
ab_one, ab_two, b_ld, b_offset, b_buffer,
n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
ConstantOne<T>(), program,
true, ab_rotated, false);
eventWaitList.push_back(eventProcessB);
}
// Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to
// modify the other triangle.
auto eventProcessC = Event();
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<T>(), program,
true, c_rotated, false);
eventWaitList.push_back(eventProcessC);
// Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary
auto kernel = Kernel(program, kernel_name);
// Sets the kernel arguments
kernel.SetArgument(0, static_cast<int>(n_ceiled));
kernel.SetArgument(1, static_cast<int>(k_ceiled));
kernel.SetArgument(2, GetRealArg(alpha));
kernel.SetArgument(3, GetRealArg(beta));
kernel.SetArgument(4, a_temp());
kernel.SetArgument(5, b_temp());
kernel.SetArgument(6, c_temp());
// 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
auto eventKernel1 = Event();
RunKernel(kernel, queue_, device_, global, local, eventKernel1.pointer(), eventWaitList);
eventWaitList.push_back(eventKernel1);
// Swaps the arguments for matrices A and B, and sets 'beta' to 1
auto one = static_cast<T>(1);
kernel.SetArgument(3, GetRealArg(one));
kernel.SetArgument(4, b_temp());
kernel.SetArgument(5, a_temp());
// Runs the kernel again
auto eventKernel2 = Event();
RunKernel(kernel, queue_, device_, global, local, eventKernel2.pointer(), eventWaitList);
eventWaitList.push_back(eventKernel2);
// Runs the post-processing kernel
auto upper = (triangle == Triangle::kUpper);
auto lower = (triangle == Triangle::kLower);
PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList,
n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
n, n, c_ld, c_offset, c_buffer,
ConstantOne<T>(), program,
false, c_rotated, false, upper, lower, false);
}
// =================================================================================================
// Compiles the templated class
template class Xsyr2k<half>;
template class Xsyr2k<float>;
template class Xsyr2k<double>;
template class Xsyr2k<float2>;
template class Xsyr2k<double2>;
// =================================================================================================
} // namespace clblast
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