This paper presents two approaches using a Block Low-Rank (BLR) compression technique
to reduce the memory footprint and/or the time-to-solution of the sparse supernodal solver
PaStiX. This flat, non-hierarchical, compression method allows to take advantage of the low-
rank property of the blocks appearing during the factorization of sparse linear systems,
which come from the discretization of partial differential equations. The proposed solver can
be used either as a direct solver at a lower precision or as a very robust preconditioner. The …