Abstract
We describe some extensions to Parallel Sparse BLAS (PSBLAS), a library of routines providing basic Linear Algebra operations needed to build iterative sparse linear system solvers on distributed-memory parallel computers. We focus on the implementation of parallel Additive Schwarz preconditioners, widely used in the solution of linear systems arising from a variety of applications. We report a performance analysis of these PSBLAS-based preconditioners on test cases arising from automotive engine simulations. We also make a comparison with equivalent software from the well-known PETSc library. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Buttari, A., D’Ambra, P., Di Serafino, D., & Filippone, S. (2006). Extending PSBLAS to build parallel schwarz preconditioners. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3732 LNCS, pp. 593–602). https://doi.org/10.1007/11558958_71
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