150 lines
3.9 KiB
C++
150 lines
3.9 KiB
C++
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
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// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
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// LICENSE and NOTICE for details. LLNL-CODE-806117.
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//
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// This file is part of the MFEM library. For more information and source code
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// availability visit https://mfem.org.
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//
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// MFEM is free software; you can redistribute it and/or modify it under the
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// terms of the BSD-3 license. We welcome feedback and contributions, see file
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// CONTRIBUTING.md for details.
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#include "pardiso.hpp"
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#ifdef MFEM_USE_MKL_PARDISO
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#include "sparsemat.hpp"
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namespace mfem
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{
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PardisoSolver::PardisoSolver()
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{
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// Indicate that default parameters are changed
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iparm[0] = 1;
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// Use METIS for fill-in reordering
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iparm[1] = 2;
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// Write the solution into the x vector data
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iparm[5] = 0;
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// Maximum number of iterative refinement steps
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iparm[7] = 2;
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// Perturb the pivot elements with 1E-13
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iparm[9] = 13;
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// Use nonsymmetric permutation
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iparm[10] = 1;
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// Perform a check on the input data
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iparm[26] = 1;
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#ifdef MFEM_USE_SINGLE
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// Single precision
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iparm[27] = 1;
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#endif
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// 0-based indexing in CSR data structure
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iparm[34] = 1;
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// Maximum number of numerical factorizations
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maxfct = 1;
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// Which factorization to use. This parameter is ignored and always assumed
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// to be equal to 1. See MKL documentation.
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mnum = 1;
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// Print statistical information in file
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msglvl = 0;
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// Initialize error flag
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error = 0;
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// Real nonsymmetric matrix
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mtype = MatType::REAL_NONSYMMETRIC;
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// Number of right hand sides
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nrhs = 1;
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}
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void PardisoSolver::SetOperator(const Operator &op)
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{
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auto mat = const_cast<SparseMatrix *>(dynamic_cast<const SparseMatrix *>(&op));
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MFEM_ASSERT(mat, "Must pass SparseMatrix as Operator");
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height = op.Height();
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width = op.Width();
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m = mat->Size();
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nnz = mat->NumNonZeroElems();
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const int *Ap = mat->HostReadI();
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const int *Ai = mat->HostReadJ();
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const real_t *Ax = mat->HostReadData();
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csr_rowptr = new int[m + 1];
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reordered_csr_colind = new int[nnz];
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reordered_csr_nzval = new real_t[nnz];
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for (int i = 0; i <= m; i++)
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{
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csr_rowptr[i] = Ap[i];
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}
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// Pardiso expects the column indices to be sorted for each row
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mat->SortColumnIndices();
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for (int i = 0; i < nnz; i++)
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{
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reordered_csr_colind[i] = Ai[i];
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reordered_csr_nzval[i] = Ax[i];
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}
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// Analyze inputs
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phase = 11;
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PARDISO(pt, &maxfct, &mnum, &mtype, &phase, &m, reordered_csr_nzval, csr_rowptr,
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reordered_csr_colind, &idum, &nrhs,
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iparm, &msglvl, &ddum, &ddum, &error);
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MFEM_ASSERT(error == 0, "Pardiso symbolic factorization error");
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// Numerical factorization
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phase = 22;
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PARDISO(pt, &maxfct, &mnum, &mtype, &phase, &m, reordered_csr_nzval, csr_rowptr,
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reordered_csr_colind, &idum, &nrhs,
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iparm, &msglvl, &ddum, &ddum, &error);
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MFEM_ASSERT(error == 0, "Pardiso numerical factorization error");
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}
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void PardisoSolver::Mult(const Vector &b, Vector &x) const
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{
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// Solve
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phase = 33;
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PARDISO(pt, &maxfct, &mnum, &mtype, &phase, &m, reordered_csr_nzval, csr_rowptr,
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reordered_csr_colind, &idum, &nrhs,
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iparm, &msglvl, b.GetData(), x.GetData(), &error);
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MFEM_ASSERT(error == 0, "Pardiso solve error");
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}
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void PardisoSolver::SetPrintLevel(int print_level)
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{
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msglvl = print_level;
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}
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void PardisoSolver::SetMatrixType(MatType mat_type)
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{
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mtype = mat_type;
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}
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PardisoSolver::~PardisoSolver()
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{
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// Release all internal memory
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phase = -1;
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PARDISO(pt, &maxfct, &mnum, &mtype, &phase, &m, reordered_csr_nzval, csr_rowptr,
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reordered_csr_colind, &idum, &nrhs,
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iparm, &msglvl, &ddum, &ddum, &error);
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MFEM_ASSERT(error == 0, "Pardiso free error");
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delete[] csr_rowptr;
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delete[] reordered_csr_colind;
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delete[] reordered_csr_nzval;
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}
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} // namespace mfem
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#endif // MFEM_USE_MKL_PARDISO
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