9415d6aa08
Thir PR adds a factorized sparse approximate inverse (FSAI) implementation on hypre, which can be used as a standalone solver, preconditioner to Krylov methods, or complex smoother to BoomerAMG. Particularly, we consider the adaptive algorithm version, where the sparsity pattern of the lower triangular factor G is built dynamically, i.e., during an iterative procedure that tries to find the best nonzero positions for a given row of G. This implementation was performed on top of the IJ interface. It uses the diagonal portion of A for constructing G, i.e., it's a block-Jacobi method in the MPI sense. List of additional changes: * Add caliper instrumentation to FSAI. * Add ZeroGuess option to FSAI. * Performance optimizations. * Add OpenMP support to FSAI. * Make internal BLAS/LAPACK functions thread-safe. * Update CMake build. * Add new test cases: beam_tet_dof459_np1, beam_hex_dof459_np2, and beam_tet_dof2475_np4. * Add documentation for FSAI. Co-authored-by: Heather Switzer <switzer4@lassen36.coral.llnl.gov> Co-authored-by: heatherms27 <hmswitzer@email.wm.edu> Co-authored-by: Sarah Osborn <30503782+osborn9@users.noreply.github.com> |
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| src | ||
| .gitignore | ||
| .readthedocs.yml | ||
| CHANGELOG | ||
| COPYRIGHT | ||
| INSTALL.md | ||
| LICENSE-APACHE | ||
| LICENSE-MIT | ||
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| README.md | ||
| SUPPORT.md | ||
HYPRE is a library of high performance preconditioners and solvers featuring multigrid methods for the solution of large, sparse linear systems of equations on massively parallel computers.
For documentation, see our readthedocs page.
To install HYPRE, please see either the documentation or the file INSTALL.md.
An overview of the HYPRE release history can be found in the file CHANGELOG.
We appreciate feedback from users. Please submit comments, suggestions, and report issues on our issues page. See also SUPPORT.md.
License
HYPRE is distributed under the terms of both the MIT license and the Apache License (Version 2.0). Users may choose either license, at their option.
All new contributions must be made under both the MIT and Apache-2.0 licenses.
See LICENSE-MIT, LICENSE-APACHE, COPYRIGHT, and NOTICE for details.
SPDX-License-Identifier: (Apache-2.0 OR MIT)
LLNL-CODE-778117