Sparse Supernodal Solver exploiting Low-Rankness Property

Abstract : In this talk, we will present recent advances on PaStiX, a supernodal sparse direct solver, which has been enhanced by the introduction of Block Low-Rank compression. We will describe different strategies leading to memory consumption gain and/or time-to-solution reduction. Finally, the implementation on top of runtime systems (Parsec, StarPU), will be compared with the static scheduling used in previous experiments.
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https://hal.inria.fr/hal-01585622
Contributor : Gregoire Pichon <>
Submitted on : Monday, October 2, 2017 - 9:13:14 PM
Last modification on : Thursday, December 13, 2018 - 6:48:02 PM

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Grégoire Pichon, Eric Darve, Mathieu Faverge, Pierre Ramet, Jean Roman. Sparse Supernodal Solver exploiting Low-Rankness Property. Sparse Days 2017, Sep 2017, Toulouse, France. ⟨hal-01585622⟩

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