Communication Dans Un Congrès Année : 2025

How effective is matrix reordering for improving performance of sparse matrix-vector multiplication?

Résumé

This work evaluates the impact of matrix reordering on the performance of sparse matrix-vector multiplication across different multicore CPU platforms. Reordering can enhance performance by optimizing the non-zero element patterns to reduce total data movement and improve the load-balancing. We examine how these gains vary over different CPUs for different reordering strategies, focusing on both sequential and parallel execution. We address multiple aspects, including appropriate measurement methodology, comparison across different kinds of reordering strategies, consistency across machines, and impact of load imbalance.

Fichier principal
Vignette du fichier
3731599.3767441.pdf (1.39 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Licence

Dates et versions

hal-05460196 , version 1 (15-01-2026)

Licence

Identifiants

Citer

Omid Asudeh, Sina Mahdipour Saravani, Fabrice Rastello, Gerald Sabin, Ponnuswamy Sadayappan. How effective is matrix reordering for improving performance of sparse matrix-vector multiplication?. SC Workshops '25: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, Nov 2025, St Louis, United States. pp.823 - 827, ⟨10.1145/3731599⟩. ⟨hal-05460196⟩
457 Consultations
113 Téléchargements

Altmetric

Partager

  • More