Using the cell broadband engine and NVIDIA 8800 GPU for computational science applications: A particle dynamics comparison

Eric C. McCreath, Ahmed El Zein, Jeremy Imholz, Alistair P. Rendell, Emily Wong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The NVIDIA 8800 Graphics Processing Unit (GPU) and the Cell Broadband Engine employ a vast amount of parallelism to produce low cost high performance systems which dwarf standard desktop processing units in terms of floating point calculations. These systems offer great potential for computational science applications. This paper compares the programming model, implementation strategies and realised performance achieved on these two systems for implementing a simple particle dynamics simulation code. Both systems were found to give considerable performance improvements over high-end uni-processor machines. The Synergistic Processing Elements (SPE), on the Cell, can not directly access main memory. This complicates initial implementation compared to the NVIDIA GPU, however, fully exploiting the complex architectures of both systems is equally challenging.

Original languageEnglish
Title of host publicationAdvances in Applied Computing and Computational Sciences - Proceedings of International Symposium on Applied Computing and Computational Sciences, ACCS 2008
EditorsLean Yu, Kin Keung Lai
PublisherGlobal Information Publisher (H.K) Co., Limited
Pages74-80
Number of pages7
ISBN (Electronic)9789889964405
Publication statusPublished - 1 Jan 2008
Externally publishedYes
Event2008 International Symposium on Applied Computing and Computational Sciences, ACCS 2008 - Hong Kong, China
Duration: 1 Aug 20083 Aug 2008

Conference

Conference2008 International Symposium on Applied Computing and Computational Sciences, ACCS 2008
CountryChina
CityHong Kong
Period1/08/083/08/08

Keywords

  • computer graphics
  • data storage equipment
  • Broadband
  • parallel programming

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