The rewrite rule machine node architecture and its performance

Patrick Lincoln, José Meseguer, Livio Ricciulli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Rewrite Rule Machine (RRM) is a massively parallel MIMD/SIMD computer designed with the explicit purpose of supporting very-high-level parallel programming with rewrite rules. The RRM’s node architecture consists of a SIMD processor, a SIMD controller, local memory, and network and I/O interfaces. A 64-node cluster board is already an attractive RRM system capable of extremely high performance on a variety of applications. A cluster is SIMD at the node level, but it is MIMD at the system level to flexibly exploit the parallelism of complex nonhomogeneous applications. In addition to reporting detailed simulation experiments used to validate the node design, we measure the performance of an RRM cluster on three relevant applications.

Original languageEnglish (US)
Title of host publicationParallel Processing
Subtitle of host publicationCONPAR 1994 - VAPP VI - 3rd Joint International Conference on Vector and Parallel Processing, Proceedings
EditorsJens Volkert, Bruno Buchberger
PublisherSpringer-Verlag
Pages509-520
Number of pages12
ISBN (Print)9783540584308
StatePublished - Jan 1 1994
Externally publishedYes
Event3rd Joint International Conference on Vector and Parallel Processing, CONPAR 1994 - VAPP VI - Linz, Austria
Duration: Sep 6 1994Sep 8 1994

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume854 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd Joint International Conference on Vector and Parallel Processing, CONPAR 1994 - VAPP VI
CountryAustria
CityLinz
Period9/6/949/8/94

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lincoln, P., Meseguer, J., & Ricciulli, L. (1994). The rewrite rule machine node architecture and its performance. In J. Volkert, & B. Buchberger (Eds.), Parallel Processing: CONPAR 1994 - VAPP VI - 3rd Joint International Conference on Vector and Parallel Processing, Proceedings (pp. 509-520). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 854 LNCS). Springer-Verlag.