High Performance by Exploiting Information Locality through Reverse Computing

Mouad Bahi 1 Christine Eisenbeis 1
1 ALCHEMY - Architectures, Languages and Compilers to Harness the End of Moore Years
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France
Abstract : In this paper we present performance results for our register rematerialization technique based on reverse recomputing. Rematerialization adds instructions and we show on one specifically designed example that reverse computing alleviates the impact of these additional instructions on performance. We also show how thread parallelism may be optimized on GPUs by performing register allocation with reverse recomputing that increases the number of threads per Streaming Multiprocessor (SM). This is done on the main kernel of Lattice Quantum ChromoDynamics (LQCD) simulation program where we gain a 10.84% speedup.
Type de document :
Rapport
[Research Report] 2011
Liste complète des métadonnées

Littérature citée [10 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00615493
Contributeur : Mouad Bahi <>
Soumis le : vendredi 19 août 2011 - 15:53:35
Dernière modification le : jeudi 11 janvier 2018 - 06:22:13
Document(s) archivé(s) le : lundi 12 novembre 2012 - 15:36:21

Fichier

bahi_information_locality.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inria-00615493, version 1

Collections

Citation

Mouad Bahi, Christine Eisenbeis. High Performance by Exploiting Information Locality through Reverse Computing. [Research Report] 2011. 〈inria-00615493〉

Partager

Métriques

Consultations de la notice

294

Téléchargements de fichiers

120