Modeling distributed data representation and its effect on parallel data accesses

Dejiang Jin, Sotirios G. Ziavras

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

PC clusters have emerged as viable alternatives for high-performance, low-cost computing. In such an environment, sharing data among processes is essential. Accessing the shared data, however, may often stall parallel executing threads. We propose a novel data representation scheme where an application data entity can be incarnated into a set of objects that are distributed in the cluster. The runtime support system manages the incarnated objects and data access is possible only via an appropriate interface. This distributed data representation facilitates parallel accesses for updates. Thus, tasks are subject to few limitations and application programs can harness high degrees of parallelism. Our PC cluster experiments prove the effectiveness of our approach.

Original languageEnglish (US)
Pages (from-to)1281-1289
Number of pages9
JournalJournal of Parallel and Distributed Computing
Volume65
Issue number10
DOIs
StatePublished - Oct 2005

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Keywords

  • Data encapsulation
  • Distributed data
  • PC cluster
  • Parallel data access
  • Super-programming model

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