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Sparse Supernodal Solver exploiting Low-Rankness Property

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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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Dates and versions

hal-01585622 , version 1 (02-10-2017)

Identifiers

  • HAL Id : hal-01585622 , version 1

Cite

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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