International audienceAmong the preprocessing steps of a sparse direct solver, reordering and block symbolic factorization are two major steps to reach a suitable granularity for BLAS kernels efficiency and runtime management. In this talk, we present a reordering strategy to increase off-diagonal block sizes. It enhances BLAS kernels and allows to handle larger tasks, reducing runtime overhead. Finally, we will comment the resulting gain in the PaStiX solver implemented over StarPU and PaRSEC
International audienceWe will discuss challenges in building clusters for the Block Low-Rank (BLR) a...
International audienceIn order to express parallelism, parallel sparse direct solvers take advantage...
International audienceSparse direct solvers using Block Low-Rank compression have been proven effici...
International audienceAmong the preprocessing steps of a sparse direct solver, reordering and block ...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
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 audienceSolving sparse linear systems is a problem that arises in many scientific appl...
International audienceSparse direct solvers is a time consuming operation required by many scientifi...
International audienceSparse direct solvers is a time consuming operation required by many scientifi...
International audienceIn this talk, we describe a preliminary fast direct solver using HODLR library...
Sparse direct solvers play a vital role in large-scale high performance scientific and engineering c...
The present work presents a strategy to increase the arithmetic intensity of the solvers. Namely, we...
International audienceTask-based programming models have been widely studied in the context of dense...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceWe will discuss challenges in building clusters for the Block Low-Rank (BLR) a...
International audienceIn order to express parallelism, parallel sparse direct solvers take advantage...
International audienceSparse direct solvers using Block Low-Rank compression have been proven effici...
International audienceAmong the preprocessing steps of a sparse direct solver, reordering and block ...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
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 audienceSolving sparse linear systems is a problem that arises in many scientific appl...
International audienceSparse direct solvers is a time consuming operation required by many scientifi...
International audienceSparse direct solvers is a time consuming operation required by many scientifi...
International audienceIn this talk, we describe a preliminary fast direct solver using HODLR library...
Sparse direct solvers play a vital role in large-scale high performance scientific and engineering c...
The present work presents a strategy to increase the arithmetic intensity of the solvers. Namely, we...
International audienceTask-based programming models have been widely studied in the context of dense...
International audienceThis paper presents two approaches using a Block Low-Rank (BLR) compression te...
International audienceWe will discuss challenges in building clusters for the Block Low-Rank (BLR) a...
International audienceIn order to express parallelism, parallel sparse direct solvers take advantage...
International audienceSparse direct solvers using Block Low-Rank compression have been proven effici...