4d9771741d
This patch mostly affects performance of the code produced by HLIFR lowering. If MATMUL argument is an array slice, then HLFIR lowering passes the slice to the runtime, whereas FIR lowering would create a contiguous temporary for the slice. Performance might be better than the generic implementation for cases where the leading dimension is contiguous. This patch improves CPU2000/178.galgel making HLFIR version faster than FIR version (due to avoiding the temporary copies for MATMUL arguments). Reviewed By: klausler Differential Revision: https://reviews.llvm.org/D159134
452 lines
18 KiB
C++
452 lines
18 KiB
C++
//===-- runtime/matmul.cpp ------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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// Implements all forms of MATMUL (Fortran 2018 16.9.124)
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//
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// There are two main entry points; one establishes a descriptor for the
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// result and allocates it, and the other expects a result descriptor that
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// points to existing storage.
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//
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// This implementation must handle all combinations of numeric types and
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// kinds (100 - 165 cases depending on the target), plus all combinations
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// of logical kinds (16). A single template undergoes many instantiations
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// to cover all of the valid possibilities.
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//
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// Places where BLAS routines could be called are marked as TODO items.
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#include "flang/Runtime/matmul.h"
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#include "terminator.h"
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#include "tools.h"
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#include "flang/Runtime/c-or-cpp.h"
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#include "flang/Runtime/cpp-type.h"
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#include "flang/Runtime/descriptor.h"
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#include <cstring>
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namespace Fortran::runtime {
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// General accumulator for any type and stride; this is not used for
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// contiguous numeric cases.
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT>
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class Accumulator {
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public:
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using Result = AccumulationType<RCAT, RKIND>;
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Accumulator(const Descriptor &x, const Descriptor &y) : x_{x}, y_{y} {}
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void Accumulate(const SubscriptValue xAt[], const SubscriptValue yAt[]) {
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if constexpr (RCAT == TypeCategory::Logical) {
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sum_ = sum_ ||
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(IsLogicalElementTrue(x_, xAt) && IsLogicalElementTrue(y_, yAt));
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} else {
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sum_ += static_cast<Result>(*x_.Element<XT>(xAt)) *
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static_cast<Result>(*y_.Element<YT>(yAt));
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}
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}
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Result GetResult() const { return sum_; }
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private:
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const Descriptor &x_, &y_;
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Result sum_{};
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};
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// Contiguous numeric matrix*matrix multiplication
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// matrix(rows,n) * matrix(n,cols) -> matrix(rows,cols)
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// Straightforward algorithm:
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// DO 1 I = 1, NROWS
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// DO 1 J = 1, NCOLS
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// RES(I,J) = 0
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// DO 1 K = 1, N
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// 1 RES(I,J) = RES(I,J) + X(I,K)*Y(K,J)
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// With loop distribution and transposition to avoid the inner sum
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// reduction and to avoid non-unit strides:
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// DO 1 I = 1, NROWS
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// DO 1 J = 1, NCOLS
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// 1 RES(I,J) = 0
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// DO 2 K = 1, N
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// DO 2 J = 1, NCOLS
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// DO 2 I = 1, NROWS
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// 2 RES(I,J) = RES(I,J) + X(I,K)*Y(K,J) ! loop-invariant last term
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT,
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bool X_HAS_STRIDED_COLUMNS, bool Y_HAS_STRIDED_COLUMNS>
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inline void MatrixTimesMatrix(CppTypeFor<RCAT, RKIND> *RESTRICT product,
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SubscriptValue rows, SubscriptValue cols, const XT *RESTRICT x,
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const YT *RESTRICT y, SubscriptValue n, std::size_t xColumnByteStride = 0,
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std::size_t yColumnByteStride = 0) {
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using ResultType = CppTypeFor<RCAT, RKIND>;
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std::memset(product, 0, rows * cols * sizeof *product);
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const XT *RESTRICT xp0{x};
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for (SubscriptValue k{0}; k < n; ++k) {
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ResultType *RESTRICT p{product};
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for (SubscriptValue j{0}; j < cols; ++j) {
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const XT *RESTRICT xp{xp0};
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ResultType yv;
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if constexpr (!Y_HAS_STRIDED_COLUMNS) {
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yv = static_cast<ResultType>(y[k + j * n]);
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} else {
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yv = static_cast<ResultType>(reinterpret_cast<const YT *>(
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reinterpret_cast<const char *>(y) + j * yColumnByteStride)[k]);
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}
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for (SubscriptValue i{0}; i < rows; ++i) {
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*p++ += static_cast<ResultType>(*xp++) * yv;
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}
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}
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if constexpr (!X_HAS_STRIDED_COLUMNS) {
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xp0 += rows;
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} else {
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xp0 = reinterpret_cast<const XT *>(
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reinterpret_cast<const char *>(xp0) + xColumnByteStride);
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}
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}
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}
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT>
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inline void MatrixTimesMatrixHelper(CppTypeFor<RCAT, RKIND> *RESTRICT product,
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SubscriptValue rows, SubscriptValue cols, const XT *RESTRICT x,
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const YT *RESTRICT y, SubscriptValue n,
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std::optional<std::size_t> xColumnByteStride,
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std::optional<std::size_t> yColumnByteStride) {
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if (!xColumnByteStride) {
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if (!yColumnByteStride) {
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MatrixTimesMatrix<RCAT, RKIND, XT, YT, false, false>(
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product, rows, cols, x, y, n);
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} else {
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MatrixTimesMatrix<RCAT, RKIND, XT, YT, false, true>(
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product, rows, cols, x, y, n, 0, *yColumnByteStride);
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}
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} else {
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if (!yColumnByteStride) {
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MatrixTimesMatrix<RCAT, RKIND, XT, YT, true, false>(
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product, rows, cols, x, y, n, *xColumnByteStride);
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} else {
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MatrixTimesMatrix<RCAT, RKIND, XT, YT, true, true>(
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product, rows, cols, x, y, n, *xColumnByteStride, *yColumnByteStride);
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}
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}
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}
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// Contiguous numeric matrix*vector multiplication
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// matrix(rows,n) * column vector(n) -> column vector(rows)
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// Straightforward algorithm:
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// DO 1 J = 1, NROWS
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// RES(J) = 0
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// DO 1 K = 1, N
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// 1 RES(J) = RES(J) + X(J,K)*Y(K)
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// With loop distribution and transposition to avoid the inner
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// sum reduction and to avoid non-unit strides:
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// DO 1 J = 1, NROWS
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// 1 RES(J) = 0
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// DO 2 K = 1, N
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// DO 2 J = 1, NROWS
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// 2 RES(J) = RES(J) + X(J,K)*Y(K)
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT,
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bool X_HAS_STRIDED_COLUMNS>
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inline void MatrixTimesVector(CppTypeFor<RCAT, RKIND> *RESTRICT product,
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SubscriptValue rows, SubscriptValue n, const XT *RESTRICT x,
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const YT *RESTRICT y, std::size_t xColumnByteStride = 0) {
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using ResultType = CppTypeFor<RCAT, RKIND>;
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std::memset(product, 0, rows * sizeof *product);
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[[maybe_unused]] const XT *RESTRICT xp0{x};
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for (SubscriptValue k{0}; k < n; ++k) {
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ResultType *RESTRICT p{product};
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auto yv{static_cast<ResultType>(*y++)};
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for (SubscriptValue j{0}; j < rows; ++j) {
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*p++ += static_cast<ResultType>(*x++) * yv;
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}
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if constexpr (X_HAS_STRIDED_COLUMNS) {
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xp0 = reinterpret_cast<const XT *>(
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reinterpret_cast<const char *>(xp0) + xColumnByteStride);
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x = xp0;
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}
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}
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}
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT>
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inline void MatrixTimesVectorHelper(CppTypeFor<RCAT, RKIND> *RESTRICT product,
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SubscriptValue rows, SubscriptValue n, const XT *RESTRICT x,
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const YT *RESTRICT y, std::optional<std::size_t> xColumnByteStride) {
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if (!xColumnByteStride) {
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MatrixTimesVector<RCAT, RKIND, XT, YT, false>(product, rows, n, x, y);
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} else {
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MatrixTimesVector<RCAT, RKIND, XT, YT, true>(
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product, rows, n, x, y, *xColumnByteStride);
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}
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}
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// Contiguous numeric vector*matrix multiplication
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// row vector(n) * matrix(n,cols) -> row vector(cols)
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// Straightforward algorithm:
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// DO 1 J = 1, NCOLS
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// RES(J) = 0
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// DO 1 K = 1, N
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// 1 RES(J) = RES(J) + X(K)*Y(K,J)
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// With loop distribution and transposition to avoid the inner
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// sum reduction and one non-unit stride (the other remains):
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// DO 1 J = 1, NCOLS
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// 1 RES(J) = 0
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// DO 2 K = 1, N
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// DO 2 J = 1, NCOLS
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// 2 RES(J) = RES(J) + X(K)*Y(K,J)
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT,
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bool Y_HAS_STRIDED_COLUMNS>
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inline void VectorTimesMatrix(CppTypeFor<RCAT, RKIND> *RESTRICT product,
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SubscriptValue n, SubscriptValue cols, const XT *RESTRICT x,
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const YT *RESTRICT y, std::size_t yColumnByteStride = 0) {
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using ResultType = CppTypeFor<RCAT, RKIND>;
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std::memset(product, 0, cols * sizeof *product);
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for (SubscriptValue k{0}; k < n; ++k) {
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ResultType *RESTRICT p{product};
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auto xv{static_cast<ResultType>(*x++)};
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const YT *RESTRICT yp{&y[k]};
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for (SubscriptValue j{0}; j < cols; ++j) {
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*p++ += xv * static_cast<ResultType>(*yp);
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if constexpr (!Y_HAS_STRIDED_COLUMNS) {
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yp += n;
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} else {
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yp = reinterpret_cast<const YT *>(
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reinterpret_cast<const char *>(yp) + yColumnByteStride);
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}
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}
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}
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}
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template <TypeCategory RCAT, int RKIND, typename XT, typename YT,
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bool SPARSE_COLUMNS = false>
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inline void VectorTimesMatrixHelper(CppTypeFor<RCAT, RKIND> *RESTRICT product,
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SubscriptValue n, SubscriptValue cols, const XT *RESTRICT x,
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const YT *RESTRICT y, std::optional<std::size_t> yColumnByteStride) {
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if (!yColumnByteStride) {
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VectorTimesMatrix<RCAT, RKIND, XT, YT, false>(product, n, cols, x, y);
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} else {
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VectorTimesMatrix<RCAT, RKIND, XT, YT, true>(
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product, n, cols, x, y, *yColumnByteStride);
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}
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}
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// Implements an instance of MATMUL for given argument types.
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template <bool IS_ALLOCATING, TypeCategory RCAT, int RKIND, typename XT,
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typename YT>
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static inline void DoMatmul(
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std::conditional_t<IS_ALLOCATING, Descriptor, const Descriptor> &result,
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const Descriptor &x, const Descriptor &y, Terminator &terminator) {
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int xRank{x.rank()};
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int yRank{y.rank()};
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int resRank{xRank + yRank - 2};
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if (xRank * yRank != 2 * resRank) {
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terminator.Crash("MATMUL: bad argument ranks (%d * %d)", xRank, yRank);
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}
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SubscriptValue extent[2]{
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xRank == 2 ? x.GetDimension(0).Extent() : y.GetDimension(1).Extent(),
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resRank == 2 ? y.GetDimension(1).Extent() : 0};
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if constexpr (IS_ALLOCATING) {
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result.Establish(
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RCAT, RKIND, nullptr, resRank, extent, CFI_attribute_allocatable);
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for (int j{0}; j < resRank; ++j) {
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result.GetDimension(j).SetBounds(1, extent[j]);
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}
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if (int stat{result.Allocate()}) {
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terminator.Crash(
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"MATMUL: could not allocate memory for result; STAT=%d", stat);
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}
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} else {
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RUNTIME_CHECK(terminator, resRank == result.rank());
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RUNTIME_CHECK(
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terminator, result.ElementBytes() == static_cast<std::size_t>(RKIND));
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RUNTIME_CHECK(terminator, result.GetDimension(0).Extent() == extent[0]);
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RUNTIME_CHECK(terminator,
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resRank == 1 || result.GetDimension(1).Extent() == extent[1]);
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}
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SubscriptValue n{x.GetDimension(xRank - 1).Extent()};
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if (n != y.GetDimension(0).Extent()) {
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terminator.Crash("MATMUL: unacceptable operand shapes (%jdx%jd, %jdx%jd)",
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static_cast<std::intmax_t>(x.GetDimension(0).Extent()),
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static_cast<std::intmax_t>(n),
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static_cast<std::intmax_t>(y.GetDimension(0).Extent()),
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static_cast<std::intmax_t>(y.GetDimension(1).Extent()));
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}
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using WriteResult =
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CppTypeFor<RCAT == TypeCategory::Logical ? TypeCategory::Integer : RCAT,
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RKIND>;
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if constexpr (RCAT != TypeCategory::Logical) {
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if (x.IsContiguous(1) && y.IsContiguous(1) &&
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(IS_ALLOCATING || result.IsContiguous())) {
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// Contiguous numeric matrices (maybe with columns
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// separated by a stride).
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std::optional<std::size_t> xColumnByteStride;
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if (!x.IsContiguous()) {
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// X's columns are strided.
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SubscriptValue xAt[2]{};
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x.GetLowerBounds(xAt);
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xAt[1]++;
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xColumnByteStride = x.SubscriptsToByteOffset(xAt);
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}
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std::optional<std::size_t> yColumnByteStride;
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if (!y.IsContiguous()) {
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// Y's columns are strided.
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SubscriptValue yAt[2]{};
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y.GetLowerBounds(yAt);
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yAt[1]++;
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yColumnByteStride = y.SubscriptsToByteOffset(yAt);
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}
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// Note that BLAS GEMM can be used for the strided
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// columns by setting proper leading dimension size.
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// This implies that the column stride is divisible
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// by the element size, which is usually true.
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if (resRank == 2) { // M*M -> M
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if (std::is_same_v<XT, YT>) {
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if constexpr (std::is_same_v<XT, float>) {
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// TODO: call BLAS-3 SGEMM
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// TODO: try using CUTLASS for device.
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} else if constexpr (std::is_same_v<XT, double>) {
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// TODO: call BLAS-3 DGEMM
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} else if constexpr (std::is_same_v<XT, std::complex<float>>) {
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// TODO: call BLAS-3 CGEMM
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} else if constexpr (std::is_same_v<XT, std::complex<double>>) {
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// TODO: call BLAS-3 ZGEMM
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}
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}
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MatrixTimesMatrixHelper<RCAT, RKIND, XT, YT>(
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result.template OffsetElement<WriteResult>(), extent[0], extent[1],
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x.OffsetElement<XT>(), y.OffsetElement<YT>(), n, xColumnByteStride,
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yColumnByteStride);
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return;
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} else if (xRank == 2) { // M*V -> V
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if (std::is_same_v<XT, YT>) {
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if constexpr (std::is_same_v<XT, float>) {
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// TODO: call BLAS-2 SGEMV(x,y)
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} else if constexpr (std::is_same_v<XT, double>) {
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// TODO: call BLAS-2 DGEMV(x,y)
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} else if constexpr (std::is_same_v<XT, std::complex<float>>) {
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// TODO: call BLAS-2 CGEMV(x,y)
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} else if constexpr (std::is_same_v<XT, std::complex<double>>) {
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// TODO: call BLAS-2 ZGEMV(x,y)
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}
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}
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MatrixTimesVectorHelper<RCAT, RKIND, XT, YT>(
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result.template OffsetElement<WriteResult>(), extent[0], n,
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x.OffsetElement<XT>(), y.OffsetElement<YT>(), xColumnByteStride);
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return;
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} else { // V*M -> V
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if (std::is_same_v<XT, YT>) {
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if constexpr (std::is_same_v<XT, float>) {
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// TODO: call BLAS-2 SGEMV(y,x)
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} else if constexpr (std::is_same_v<XT, double>) {
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// TODO: call BLAS-2 DGEMV(y,x)
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} else if constexpr (std::is_same_v<XT, std::complex<float>>) {
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// TODO: call BLAS-2 CGEMV(y,x)
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} else if constexpr (std::is_same_v<XT, std::complex<double>>) {
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// TODO: call BLAS-2 ZGEMV(y,x)
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}
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}
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VectorTimesMatrixHelper<RCAT, RKIND, XT, YT>(
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result.template OffsetElement<WriteResult>(), n, extent[0],
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x.OffsetElement<XT>(), y.OffsetElement<YT>(), yColumnByteStride);
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return;
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}
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}
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}
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// General algorithms for LOGICAL and noncontiguity
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SubscriptValue xAt[2], yAt[2], resAt[2];
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x.GetLowerBounds(xAt);
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y.GetLowerBounds(yAt);
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result.GetLowerBounds(resAt);
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if (resRank == 2) { // M*M -> M
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SubscriptValue x1{xAt[1]}, y0{yAt[0]}, y1{yAt[1]}, res1{resAt[1]};
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for (SubscriptValue i{0}; i < extent[0]; ++i) {
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for (SubscriptValue j{0}; j < extent[1]; ++j) {
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Accumulator<RCAT, RKIND, XT, YT> accumulator{x, y};
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yAt[1] = y1 + j;
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for (SubscriptValue k{0}; k < n; ++k) {
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xAt[1] = x1 + k;
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yAt[0] = y0 + k;
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accumulator.Accumulate(xAt, yAt);
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}
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resAt[1] = res1 + j;
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*result.template Element<WriteResult>(resAt) = accumulator.GetResult();
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}
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++resAt[0];
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++xAt[0];
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}
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} else if (xRank == 2) { // M*V -> V
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SubscriptValue x1{xAt[1]}, y0{yAt[0]};
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for (SubscriptValue j{0}; j < extent[0]; ++j) {
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Accumulator<RCAT, RKIND, XT, YT> accumulator{x, y};
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for (SubscriptValue k{0}; k < n; ++k) {
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xAt[1] = x1 + k;
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yAt[0] = y0 + k;
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accumulator.Accumulate(xAt, yAt);
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}
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*result.template Element<WriteResult>(resAt) = accumulator.GetResult();
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++resAt[0];
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++xAt[0];
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}
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} else { // V*M -> V
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SubscriptValue x0{xAt[0]}, y0{yAt[0]};
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for (SubscriptValue j{0}; j < extent[0]; ++j) {
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Accumulator<RCAT, RKIND, XT, YT> accumulator{x, y};
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for (SubscriptValue k{0}; k < n; ++k) {
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xAt[0] = x0 + k;
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yAt[0] = y0 + k;
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accumulator.Accumulate(xAt, yAt);
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}
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*result.template Element<WriteResult>(resAt) = accumulator.GetResult();
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++resAt[0];
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++yAt[1];
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}
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}
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}
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// Maps the dynamic type information from the arguments' descriptors
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// to the right instantiation of DoMatmul() for valid combinations of
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// types.
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template <bool IS_ALLOCATING> struct Matmul {
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using ResultDescriptor =
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std::conditional_t<IS_ALLOCATING, Descriptor, const Descriptor>;
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template <TypeCategory XCAT, int XKIND> struct MM1 {
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template <TypeCategory YCAT, int YKIND> struct MM2 {
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void operator()(ResultDescriptor &result, const Descriptor &x,
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const Descriptor &y, Terminator &terminator) const {
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if constexpr (constexpr auto resultType{
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GetResultType(XCAT, XKIND, YCAT, YKIND)}) {
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if constexpr (common::IsNumericTypeCategory(resultType->first) ||
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resultType->first == TypeCategory::Logical) {
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return DoMatmul<IS_ALLOCATING, resultType->first,
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resultType->second, CppTypeFor<XCAT, XKIND>,
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CppTypeFor<YCAT, YKIND>>(result, x, y, terminator);
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}
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}
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terminator.Crash("MATMUL: bad operand types (%d(%d), %d(%d))",
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static_cast<int>(XCAT), XKIND, static_cast<int>(YCAT), YKIND);
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}
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};
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void operator()(ResultDescriptor &result, const Descriptor &x,
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const Descriptor &y, Terminator &terminator, TypeCategory yCat,
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int yKind) const {
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ApplyType<MM2, void>(yCat, yKind, terminator, result, x, y, terminator);
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}
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};
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void operator()(ResultDescriptor &result, const Descriptor &x,
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const Descriptor &y, const char *sourceFile, int line) const {
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Terminator terminator{sourceFile, line};
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auto xCatKind{x.type().GetCategoryAndKind()};
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auto yCatKind{y.type().GetCategoryAndKind()};
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RUNTIME_CHECK(terminator, xCatKind.has_value() && yCatKind.has_value());
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ApplyType<MM1, void>(xCatKind->first, xCatKind->second, terminator, result,
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x, y, terminator, yCatKind->first, yCatKind->second);
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}
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};
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extern "C" {
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void RTNAME(Matmul)(Descriptor &result, const Descriptor &x,
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const Descriptor &y, const char *sourceFile, int line) {
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Matmul<true>{}(result, x, y, sourceFile, line);
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}
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void RTNAME(MatmulDirect)(const Descriptor &result, const Descriptor &x,
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const Descriptor &y, const char *sourceFile, int line) {
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Matmul<false>{}(result, x, y, sourceFile, line);
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}
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} // extern "C"
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} // namespace Fortran::runtime
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