| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2026 Rasmus Munk Larsen <rmlarsen@gmail.com> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| // SPDX-License-Identifier: MPL-2.0 |
| |
| // BLAS Level 3 expression types for gpu::DeviceMatrix beyond GEMM: triangular |
| // solve, self-adjoint multiply, and rank-k update. |
| |
| #ifndef EIGEN_GPU_DEVICE_BLAS_EXPR_H |
| #define EIGEN_GPU_DEVICE_BLAS_EXPR_H |
| |
| // IWYU pragma: private |
| #include "./InternalHeaderCheck.h" |
| |
| #include <functional> |
| |
| #include "./FwdDecl.h" |
| |
| namespace Eigen { |
| namespace gpu { |
| |
| /** d_A.triangularView<Lower>(), whose solve() builds a TrsmExpr. */ |
| template <typename Scalar_, int UpLo_> |
| class TriangularView { |
| public: |
| using Scalar = Scalar_; |
| static constexpr int UpLo = UpLo_; |
| |
| explicit TriangularView(const DeviceMatrix<Scalar>& m) : mat_(m) {} |
| const DeviceMatrix<Scalar>& matrix() const { return mat_; } |
| |
| TrsmExpr<Scalar, UpLo_> solve(const DeviceMatrix<Scalar>& rhs) const { return {mat_, rhs}; } |
| |
| private: |
| std::reference_wrapper<const DeviceMatrix<Scalar>> mat_; |
| }; |
| |
| /** triangularView<UpLo>().solve(B), dispatched to cublasXtrsm. */ |
| template <typename Scalar_, int UpLo_> |
| class TrsmExpr { |
| public: |
| using Scalar = Scalar_; |
| static constexpr int UpLo = UpLo_; |
| |
| TrsmExpr(const DeviceMatrix<Scalar>& A, const DeviceMatrix<Scalar>& B) : A_(A), B_(B) {} |
| const DeviceMatrix<Scalar>& matrix() const { return A_; } |
| const DeviceMatrix<Scalar>& rhs() const { return B_; } |
| |
| private: |
| std::reference_wrapper<const DeviceMatrix<Scalar>> A_; |
| std::reference_wrapper<const DeviceMatrix<Scalar>> B_; |
| }; |
| |
| /** d_A.selfadjointView<Lower>(), which supports view * d_B and rankUpdate(). */ |
| template <typename Scalar_, int UpLo_> |
| class SelfAdjointView { |
| public: |
| using Scalar = Scalar_; |
| using RealScalar = typename NumTraits<Scalar>::Real; |
| static constexpr int UpLo = UpLo_; |
| |
| explicit SelfAdjointView(DeviceMatrix<Scalar>& m) : mat_(m) {} |
| const DeviceMatrix<Scalar>& matrix() const { return mat_; } |
| DeviceMatrix<Scalar>& matrix() { return mat_; } |
| |
| /** C = alpha * A * A^H + C, writing only the UpLo triangle. Maps to |
| * cublasXsyrk (real) or cublasXherk (complex). */ |
| void rankUpdate(const DeviceMatrix<Scalar>& A, RealScalar alpha = RealScalar(1)); |
| |
| private: |
| std::reference_wrapper<DeviceMatrix<Scalar>> mat_; |
| }; |
| |
| /** Const variant, supporting multiplication but not rankUpdate. */ |
| template <typename Scalar_, int UpLo_> |
| class ConstSelfAdjointView { |
| public: |
| using Scalar = Scalar_; |
| static constexpr int UpLo = UpLo_; |
| |
| explicit ConstSelfAdjointView(const DeviceMatrix<Scalar>& m) : mat_(m) {} |
| const DeviceMatrix<Scalar>& matrix() const { return mat_; } |
| |
| private: |
| std::reference_wrapper<const DeviceMatrix<Scalar>> mat_; |
| }; |
| |
| /** selfadjointView<UpLo>() * B, dispatched to cublasXsymm (real) or |
| * cublasXhemm (complex). */ |
| template <typename Scalar_, int UpLo_> |
| class SymmExpr { |
| public: |
| using Scalar = Scalar_; |
| static constexpr int UpLo = UpLo_; |
| |
| SymmExpr(const DeviceMatrix<Scalar>& A, const DeviceMatrix<Scalar>& B) : A_(A), B_(B) {} |
| const DeviceMatrix<Scalar>& matrix() const { return A_; } |
| const DeviceMatrix<Scalar>& rhs() const { return B_; } |
| |
| private: |
| std::reference_wrapper<const DeviceMatrix<Scalar>> A_; |
| std::reference_wrapper<const DeviceMatrix<Scalar>> B_; |
| }; |
| |
| template <typename S, int UpLo> |
| SymmExpr<S, UpLo> operator*(const SelfAdjointView<S, UpLo>& a, const DeviceMatrix<S>& b) { |
| return {a.matrix(), b}; |
| } |
| template <typename S, int UpLo> |
| SymmExpr<S, UpLo> operator*(const ConstSelfAdjointView<S, UpLo>& a, const DeviceMatrix<S>& b) { |
| return {a.matrix(), b}; |
| } |
| |
| /** C.rankUpdate(A), i.e. C += A * A^H, dispatched to cublasXsyrk (real) or |
| * cublasXherk (complex). */ |
| template <typename Scalar_, int UpLo_> |
| class SyrkExpr { |
| public: |
| using Scalar = Scalar_; |
| static constexpr int UpLo = UpLo_; |
| |
| SyrkExpr(const DeviceMatrix<Scalar>& A) : A_(A) {} |
| const DeviceMatrix<Scalar>& matrix() const { return A_; } |
| |
| private: |
| std::reference_wrapper<const DeviceMatrix<Scalar>> A_; |
| }; |
| |
| } // namespace gpu |
| } // namespace Eigen |
| |
| #endif // EIGEN_GPU_DEVICE_BLAS_EXPR_H |