Reordering Strategy for Blocking Optimization in Sparse Linear Solvers
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Sparse direct solvers is a time consuming operation required by many scientific applications to simulate physical problems. By its important overall cost, many studies tried to …
The complexity of the hardware architectures of modern supercomputers led the community of developers of scientific libraries to adopt new parallel programming paradigms. Among …
Among 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 …
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In this thesis, we focus on the parallel solving of large sparse linear systems. Our main interest is on direct-iterative hybrid solvers such as HIPS, MAPHYS, PDSLIN or SHYLU, …
In the context of solving sparse linear systems, an ordering process partitions the matrix graph to minimize both fill-in and computational cost. We found that the ordering …
In the context of hybrid sparse linear solvers based on domain decomposition and Schur complement approaches, getting a domain decomposition tool leading to a good balancing of …
In this talk we will discuss our research activities on the design of parallel linear solvers for large scale problems that range from dense linear algebra, to parallel sparse …
In the context of solving sparse linear systems, an ordering process partitions the matrix graph to minimize both fill-in and computational cost. We found that the ordering …