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Sparse Supernodal Solver Using Hierarchical Compression

Abstract : In this talk, we present the PaStiX sparse supernodal solver, using hierarchical compression to reduce the burden on large blocks appearing during the nested dissection process. To improve the efficiency of our sparse update kernel for both BLR (block low rank) and HODLR (hierarchically off-diagonal low-rank), we investigate to BDLR (boundary distance low-rank) method to preselect rows and columns in the low-rank approximation algorithm. We will also discuss ordering strategies to enhance data locality and compressibility.
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Contributor : Pierre Ramet Connect in order to contact the contributor
Submitted on : Thursday, December 22, 2016 - 10:21:54 AM
Last modification on : Friday, November 18, 2022 - 9:24:23 AM


  • HAL Id : hal-01421368, version 1



Grégoire Pichon, Eric Darve, Mathieu Faverge, Pierre Ramet, Jean Roman. Sparse Supernodal Solver Using Hierarchical Compression. Workshop on Fast Direct Solvers, Nov 2016, Purdue, United States. ⟨hal-01421368⟩



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