Fine-grain parallelism using multi-core, Cell/BE, and GPU systems

Frederico Pratas, Pedro Trancoso, Leonel Sousa, Alexandros Stamatakis, Guochun Shi, Volodymyr Kindratenko

Research output: Contribution to journalArticlepeer-review

Abstract

Currently, we are facing a situation where applications exhibit increasing computational demands and where a large variety of parallel processor systems are available. In this paper we focus on exploiting fine-grain parallelism for three applications with distinct characteristics: a Bioinformatics application (MrBayes), a Molecular Dynamics application (NAMD), and a database application (TPC-H). We assess, side-by-side, the performance of the three applications on general-purpose multi-core processors, the Cell Broadband Engine (Cell/BE), and Graphics Processing Units (GPU). Our results indicate that application performance depends on the characteristics of the parallel architectures and on the computational requirements of the core functions of the respective applications. For MrBayes the best overall performance is achieved on general-purpose multi-core processors, for NAMD on the Cell/BE, and for TPC-H on GPUs.

Original languageEnglish (US)
Pages (from-to)365-390
Number of pages26
JournalParallel Computing
Volume38
Issue number8
DOIs
StatePublished - Aug 2012

Keywords

  • Database workloads
  • Fine-grain parallelism
  • Multi-core acelerators
  • Multi-core processors
  • Performance evaluation
  • Scientific workloads

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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