On the scalability of hypergraph models for sparse matrix partitioning - ENS de Lyon - École normale supérieure de Lyon
Communication Dans Un Congrès Année : 2010

On the scalability of hypergraph models for sparse matrix partitioning

Résumé

We investigate the scalability of the hypergraph-based sparse matrix partitioning methods with respect to the increasing sizes of matrices and number of nonzeros. We propose a method to rowwise partition the matrices that correspond to the discretization of two-dimensional domains with the five-point stencil. The proposed method obtains perfect load balance and achieves very good total communication volume. We investigate the behaviour of the hypergraph-based rowwise partitioning method with respect to the proposed method, in an attempt to understand how scalable the former method is. In another set of experiments, we work on general sparse matrices under different scenarios to understand the scalability of various hypergraph-based one- and two-dimensional matrix partitioning methods.
Fichier principal
Vignette du fichier
ucca10.pdf (1.1 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

ensl-00529088 , version 1 (24-10-2010)

Identifiants

Citer

Bora Uçar, Umit V. Catalyurek. On the scalability of hypergraph models for sparse matrix partitioning. 18th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2010), IEEE, Feb 2010, Pisa, Italy. pp.593-600, ⟨10.1109/PDP.2010.92⟩. ⟨ensl-00529088⟩
192 Consultations
348 Téléchargements

Altmetric

Partager

More