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First version of MATX Sparse-Direct-Solve (using dispatch to cuDSS) (#…
…849) * First version of MATX Sparse-Direct-Solve (using dispatch to cuDSS)
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| //////////////////////////////////////////////////////////////////////////////// | ||
| // BSD 3-Clause License | ||
| // | ||
| // Copyright (c) 2025, NVIDIA Corporation | ||
| // All rights reserved. | ||
| // | ||
| // Redistribution and use in source and binary forms, with or without | ||
| // modification, are permitted provided that the following conditions are met: | ||
| // | ||
| // 1. Redistributions of source code must retain the above copyright notice, this | ||
| // list of conditions and the following disclaimer. | ||
| // | ||
| // 2. Redistributions in binary form must reproduce the above copyright notice, | ||
| // this list of conditions and the following disclaimer in the documentation | ||
| // and/or other materials provided with the distribution. | ||
| // | ||
| // 3. Neither the name of the copyright holder nor the names of its | ||
| // contributors may be used to endorse or promote products derived from | ||
| // this software without specific prior written permission. | ||
| // | ||
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | ||
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
| // DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE | ||
| // FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL | ||
| // DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR | ||
| // SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| // CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, | ||
| // OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
| // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
| ///////////////////////////////////////////////////////////////////////////////// | ||
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| #pragma once | ||
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| #include "matx/core/type_utils.h" | ||
| #include "matx/operators/base_operator.h" | ||
| #ifdef MATX_EN_CUDSS | ||
| #include "matx/transforms/solve/solve_cudss.h" | ||
| #endif | ||
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| namespace matx { | ||
| namespace detail { | ||
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| template <typename OpA, typename OpB> | ||
| class SolveOp : public BaseOp<SolveOp<OpA, OpB>> { | ||
| private: | ||
| typename detail::base_type_t<OpA> a_; | ||
| typename detail::base_type_t<OpB> b_; | ||
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| static constexpr int out_rank = OpB::Rank(); | ||
| cuda::std::array<index_t, out_rank> out_dims_; | ||
| mutable detail::tensor_impl_t<typename OpA::value_type, out_rank> tmp_out_; | ||
| mutable typename OpA::value_type *ptr = nullptr; | ||
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| public: | ||
| using matxop = bool; | ||
| using matx_transform_op = bool; | ||
| using solve_xform_op = bool; | ||
| using value_type = typename OpA::value_type; | ||
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| __MATX_INLINE__ SolveOp(const OpA &a, const OpB &b) : a_(a), b_(b) { | ||
| for (int r = 0, rank = Rank(); r < rank; r++) { | ||
| out_dims_[r] = b_.Size(r); | ||
| } | ||
| } | ||
|
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| __MATX_INLINE__ std::string str() const { | ||
| return "solve(" + get_type_str(a_) + "," + get_type_str(b_) + ")"; | ||
| } | ||
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| __MATX_HOST__ __MATX_INLINE__ auto Data() const noexcept { return ptr; } | ||
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| template <typename... Is> | ||
| __MATX_INLINE__ __MATX_DEVICE__ __MATX_HOST__ decltype(auto) | ||
| operator()(Is... indices) const { | ||
| return tmp_out_(indices...); | ||
| } | ||
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| static __MATX_INLINE__ constexpr __MATX_HOST__ __MATX_DEVICE__ int32_t | ||
| Rank() { | ||
| return remove_cvref_t<OpB>::Rank(); | ||
| } | ||
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| constexpr __MATX_INLINE__ __MATX_HOST__ __MATX_DEVICE__ index_t | ||
| Size(int dim) const { | ||
| return out_dims_[dim]; | ||
| } | ||
|
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| template <typename Out, typename Executor> | ||
| void Exec([[maybe_unused]] Out &&out, [[maybe_unused]] Executor &&ex) const { | ||
| static_assert(!is_sparse_tensor_v<OpB>, "sparse rhs not implemented"); | ||
| if constexpr (is_sparse_tensor_v<OpA>) { | ||
| #ifdef MATX_EN_CUDSS | ||
| sparse_solve_impl(cuda::std::get<0>(out), a_, b_, ex); | ||
| #else | ||
| MATX_THROW(matxNotSupported, "Sparse direct solver requires cuDSS"); | ||
| #endif | ||
| } else { | ||
| MATX_THROW(matxNotSupported, | ||
| "Direct solver currently only supports sparse system"); | ||
| } | ||
| } | ||
|
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| template <typename ShapeType, typename Executor> | ||
| __MATX_INLINE__ void InnerPreRun([[maybe_unused]] ShapeType &&shape, | ||
| [[maybe_unused]] Executor &&ex) const noexcept { | ||
| static_assert(is_sparse_tensor_v<OpA>, | ||
| "Direct solver currently only supports sparse system"); | ||
| if constexpr (is_matx_op<OpB>()) { | ||
| b_.PreRun(std::forward<ShapeType>(shape), std::forward<Executor>(ex)); | ||
| } | ||
| } | ||
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| template <typename ShapeType, typename Executor> | ||
| __MATX_INLINE__ void PreRun([[maybe_unused]] ShapeType &&shape, | ||
| [[maybe_unused]] Executor &&ex) const noexcept { | ||
| InnerPreRun(std::forward<ShapeType>(shape), std::forward<Executor>(ex)); | ||
| detail::AllocateTempTensor(tmp_out_, std::forward<Executor>(ex), out_dims_, | ||
| &ptr); | ||
| Exec(cuda::std::make_tuple(tmp_out_), std::forward<Executor>(ex)); | ||
| } | ||
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| template <typename ShapeType, typename Executor> | ||
| __MATX_INLINE__ void PostRun([[maybe_unused]] ShapeType &&shape, | ||
| [[maybe_unused]]Executor &&ex) const noexcept { | ||
| static_assert(is_sparse_tensor_v<OpA>, | ||
| "Direct solver currently only supports sparse system"); | ||
| if constexpr (is_matx_op<OpB>()) { | ||
| b_.PostRun(std::forward<ShapeType>(shape), std::forward<Executor>(ex)); | ||
| } | ||
| matxFree(ptr); | ||
| } | ||
| }; | ||
|
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| } // end namespace detail | ||
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| /** | ||
| * Run a direct SOLVE (viz. X = solve(A, B) solves system AX=B for unknown X). | ||
| * | ||
| * Note that currently, this operation is only implemented for solving | ||
| * a linear system with a very **sparse** matrix A. | ||
| * | ||
| * @tparam OpA | ||
| * Data type of A tensor (sparse) | ||
| * @tparam OpB | ||
| * Data type of B tensor | ||
| * | ||
| * @param A | ||
| * A Sparse tensor with system coefficients | ||
| * @param B | ||
| * B Dense tensor of known values | ||
| * | ||
| * @return | ||
| * Operator that produces the output tensor X with the solution | ||
| */ | ||
| template <typename OpA, typename OpB> | ||
| __MATX_INLINE__ auto solve(const OpA &A, const OpB &B) { | ||
| return detail::SolveOp(A, B); | ||
| } | ||
|
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| } // end namespace matx |
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