1664a340f8
This PR enables the use of Krylov methods for solving linear systems with multi-component vectors. Regression tests have been added on src/test/TEST_ij/vector.sh. Additionally, hypre_ParCSRDiagScaleVector and hypreDevice_DiagScaleVector have been extended to work with multi-component vectors. * Small changes to support multi-component Krylov algorithms. This seems to work with GMRES. * Extend hypre_ParCSRDiagScaleVector to multicomponent vectors * Extend hypreDevice_DiagScaleVector to multicomponent vectors * Test Krylov solvers support for multi-component vectors * Update result for the final residual norm (Tux) * Add hypreGPUKernel_CSRMatvecShuffleGT8 and update hypreDevice_CSRMatrixMatvec with new kernel dispatching strategy * Add number of matvecs as a command line option for the IJ driver * Add vector.saved.lassen and vector.saved.arcticus files * Run astyle Co-authored-by: Paul Mullowney <Paul.Mullowney@nrel.gov> Co-authored-by: Wayne Mitchell <mitchell82@llnl.gov> |
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| AUTOTEST | ||
| src | ||
| .gitignore | ||
| .readthedocs.yml | ||
| CHANGELOG | ||
| COPYRIGHT | ||
| INSTALL.md | ||
| LICENSE-APACHE | ||
| LICENSE-MIT | ||
| NOTICE | ||
| 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