Block Low-rank Algebraic Clustering for Sparse Direct Solvers - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2019

Block Low-rank Algebraic Clustering for Sparse Direct Solvers


We will discuss challenges in building clusters for the Block Low-Rank (BLR) approach, for nodes inside separators appearing during the factorization of sparse matrices. We will illustrate limitations for methods that consider only intra-separators connectivity (i.e., k-way and recursive bisection) as well as methods focusing only on reducing the number of updates between separators. The new strategy we propose considers interactions between a separator and its children in the nested dissection. It allows reducing the computational cost of BLR, and the number of off-diagonal blocks. We demonstrate that this method enhances the BLR strategies in the sparse direct supernodal solver PaStiX, and discuss how it can be extended to low-rank formats with more than one level of hierarchy.
No file

Dates and versions

hal-01956962 , version 1 (16-12-2018)


  • HAL Id : hal-01956962 , version 1


Grégoire Pichon, Eric Darve, Mathieu Faverge, Pierre Ramet, Jean Roman. Block Low-rank Algebraic Clustering for Sparse Direct Solvers. SIAM Conference on Computational Science and Engineering (CSE19), Feb 2019, Spokane, United States. ⟨hal-01956962⟩
128 View
0 Download


Gmail Facebook X LinkedIn More