Sparse Supernodal Solver exploiting Low-Rankness Property

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.

Conference paper