Towards a framework for abstracting accelerators in parallel applications: Experience with cell

David M. Kunzman, Laxmikant V. Kalé

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

Abstract

While accelerators have become more prevalent in recent years, they are still considered hard to program. In this work, we extend a framework for parallel programming so that programmers can easily take advantage of the Cell processor's Synergistic Processing Elements (SPEs) as seamlessly as possible. Using this framework, the same application code can be compiled and executed on multiple platforms, including x86-based and Cell-based clusters. Furthermore, our model allows independently developed libraries to efficiently time-share one or more SPEs by interleaving work from multiple libraries. To demonstrate the framework, we present performance data for an example molecular dynamics (MD) application. When compared to a single Xeon core utilizing streaming SIMD extensions (SSE), the MD program achieves a speedup of 5.74 on a single Cell chip (with 8 SPEs). In comparison, a similar speedup of 5.89 is achieved using six Xeon (x86) cores.

Original languageEnglish (US)
Title of host publicationProceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC '09
DOIs
StatePublished - Dec 1 2009
EventConference on High Performance Computing Networking, Storage and Analysis, SC '09 - Portland, OR, United States
Duration: Nov 14 2009Nov 20 2009

Publication series

NameProceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC '09

Other

OtherConference on High Performance Computing Networking, Storage and Analysis, SC '09
CountryUnited States
CityPortland, OR
Period11/14/0911/20/09

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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