Compilation of a Specialized Functional Language for Massively Parallel Computers

Pascal Fradet 1 Julien Mallet 1
1 Lande - Logiciel : ANalyse et DEveloppement
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We propose a parallel specialized language that ensures portable and cost-predictable implementations on parallel computers. The language is basically a first-order, recursion-less, strict functional language equipped with a collection of higher-order functions or skeletons. These skeletons apply on (nested) vectors and can be grouped in four classes: computation, reorganization, communication, and mask skeletons. The compilation process is described as a series of transformations and analyses leading to SPMD-like functional programs which can be directly translated into real parallel code. The language restrictions enforce a programming discipline whose benefit is to allow a static, symbolic, and accurate cost analysis. The parallel cost takes into account both load balancing and communications, and can be statically evaluated even when the actual size of vectors or the number of processors are unknown. It is used to automatically select the best data distribution among a set of standard distributions. Interestingl- y, this work can be seen as a cross fertilization between techniques developed within the FORTRAN parallelization, skeleton, and functional programming communities.
Type de document :
Rapport
[Research Report] RR-3894, INRIA. 2000
Liste complète des métadonnées

https://hal.inria.fr/inria-00072760
Contributeur : Rapport de Recherche Inria <>
Soumis le : mercredi 24 mai 2006 - 10:49:32
Dernière modification le : mercredi 16 mai 2018 - 11:23:03
Document(s) archivé(s) le : dimanche 4 avril 2010 - 21:23:56

Fichiers

Identifiants

  • HAL Id : inria-00072760, version 1

Citation

Pascal Fradet, Julien Mallet. Compilation of a Specialized Functional Language for Massively Parallel Computers. [Research Report] RR-3894, INRIA. 2000. 〈inria-00072760〉

Partager

Métriques

Consultations de la notice

248

Téléchargements de fichiers

308