GpuSparseLU.h

// 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
 
// GPU sparse LU factorization via cuDSS, with pivoting, for general
// (non-symmetric) matrices.
 
#ifndef EIGEN_GPU_SPARSE_LU_H
#define EIGEN_GPU_SPARSE_LU_H
 
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
 
#include "./GpuSparseSolverBase.h"
 
namespace Eigen {
namespace gpu {

template <typename Scalar_>
class SparseLU : public internal::SparseSolverBase<Scalar_, SparseLU<Scalar_>> {
  using Base = internal::SparseSolverBase<Scalar_, SparseLU>;
  friend Base;
 
 public:
  using Scalar = Scalar_;
 
  SparseLU() = default;

  explicit SparseLU(Context& ctx) : Base(ctx) {}
 
  template <typename InputType>
  explicit SparseLU(const SparseMatrixBase<InputType>& A) {
    this->compute(A);
  }

  template <typename InputType>
  SparseLU(Context& ctx, const SparseMatrixBase<InputType>& A) : Base(ctx) {
    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 gpu
}  // namespace Eigen
 
#endif  // EIGEN_GPU_SPARSE_LU_H