FSAI implementation on CPUs (#610)
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>
2022-04-06 02:18:39 +08:00
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TEST_ij/!(fsai).sh
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