As the core of a large number of simulation tools, the resolution of large linear systems often represents the dominant part of the computing time. Massively parallel versions are …
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Task-based programming models have been widely studied in the context of dense linear algebra, but remains less studied for the more complex sparse solvers. In this talk, we will …
In this talk, we adress the Block Low-Rank (BLR) clustering problem, to cluster unknowns within separators appearing during the factorization of sparse matrices. We show that …
In this talk, we present new ordering heuristics to perform block low-rank clustering in supernodes issued from the nested dissection. As kway partitioning within supernodes does …
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 …
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