International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchical compression to reduce the burden on large blocks appearing during the nested dissection process. To improve the efficiency of our sparse update kernel for both BLR (block low rank) and HODLR (hierarchically off-diagonal low-rank), we investigate to BDLR (boundary distance low-rank) method to preselect rows and columns in the low-rank approximation algorithm. We will also discuss ordering strategies to enhance data locality and compressibility
Solving sparse linear systems is a problem that arises in many scientific applications, and sparse d...
International audienceWhen solving large sparse linear systems, both the amount of memory needed and...
International audienceSparse direct solvers using Block Low-Rank compression have been proven effici...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceLow-rank compression techniques are very promising for reducing memory footpri...
Through the recent improvements toward exascale supercomputer systems, huge computations can be perf...
International audienceIn this talk, we describe a preliminary fast direct solver using HODLR library...
International audienceWe will discuss challenges in building clusters for the Block Low-Rank (BLR) a...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
National audienceIn this talk, we present the use of PaStiX sparse direct solver in a Schwarz method...
This paper presents two approaches using a Block Low-Rank (BLR) compressiontechnique to reduce the m...
Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the sup...
Solving sparse linear systems is a problem that arises in many scientific applications, and sparse d...
International audienceWhen solving large sparse linear systems, both the amount of memory needed and...
International audienceSparse direct solvers using Block Low-Rank compression have been proven effici...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceIn this talk, we present the PaStiX sparse supernodal solver, using hierarchic...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceLow-rank compression techniques are very promising for reducing memory footpri...
Through the recent improvements toward exascale supercomputer systems, huge computations can be perf...
International audienceIn this talk, we describe a preliminary fast direct solver using HODLR library...
International audienceWe will discuss challenges in building clusters for the Block Low-Rank (BLR) a...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
National audienceIn this talk, we present the use of PaStiX sparse direct solver in a Schwarz method...
This paper presents two approaches using a Block Low-Rank (BLR) compressiontechnique to reduce the m...
Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the sup...
Solving sparse linear systems is a problem that arises in many scientific applications, and sparse d...
International audienceWhen solving large sparse linear systems, both the amount of memory needed and...
International audienceSparse direct solvers using Block Low-Rank compression have been proven effici...