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eigen/Eigen/src/GPU/GpuSparseLU.h

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// 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/.
// GPU sparse LU factorization via cuDSS.
//
// For general (non-symmetric) sparse matrices. Uses pivoting.
// Same three-phase workflow as GpuSparseLLT.
//
// Usage:
// GpuSparseLU<double> lu(A); // analyze + factorize
// VectorXd x = lu.solve(b); // solve
#ifndef EIGEN_GPU_SPARSE_LU_H
#define EIGEN_GPU_SPARSE_LU_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
#include "./GpuSparseSolverBase.h"
namespace Eigen {
/** GPU sparse LU factorization (general matrices).
*
* Wraps cuDSS with CUDSS_MTYPE_GENERAL and CUDSS_MVIEW_FULL.
* Accepts ColMajor SparseMatrix (CSC); internally converts to RowMajor
* CSR since cuDSS requires CSR input.
*
* \tparam Scalar_ float, double, complex<float>, or complex<double>
*/
template <typename Scalar_>
class GpuSparseLU : public internal::GpuSparseSolverBase<Scalar_, GpuSparseLU<Scalar_>> {
using Base = internal::GpuSparseSolverBase<Scalar_, GpuSparseLU>;
friend Base;
public:
using Scalar = Scalar_;
GpuSparseLU() = default;
template <typename InputType>
explicit GpuSparseLU(const SparseMatrixBase<InputType>& A) {
this->compute(A);
}
static constexpr bool needs_csr_conversion() { return true; }
static constexpr cudssMatrixType_t cudss_matrix_type() { return CUDSS_MTYPE_GENERAL; }
static constexpr cudssMatrixViewType_t cudss_matrix_view() { return CUDSS_MVIEW_FULL; }
};
} // namespace Eigen
#endif // EIGEN_GPU_SPARSE_LU_H