Robust scalability analysis and SPM case studies

Dejiang Jin, Sotirios G. Ziavras

Research output: Contribution to journalArticlepeer-review

Abstract

Scalability has become an attribute of paramount importance for computer systems used in business, scientific and engineering applications. Although scalability has been widely discussed, especially for pure parallel computer systems, it conveniently focuses on improving performance when increasing the number of computing processors. In fact, the term "scalable" is so much abused that it has become a marketing tool for computer vendors independent of the system's technical qualifications. Since the primary objective of scalability analysis is to determine how well a system can work on larger problems with an increase in its size, we introduce here a generic definition of scalability. For illustrative purposes only, we apply this definition to PC clusters, a rather difficult subject due to their long communication latencies. Since scalability does not solely depend on the system architecture but also on the application programs and their actual management by the run-time environment, for the sake of illustration, we evaluate scalability for programs developed under the super-programming model (SPM) (Jin and Ziavras in IEEE Trans. Parallel Distrib. Syst. 15(9):783-794, 2004; J. Parallel Distrib. Comput. 65(10):1281-1289, 2005; IEICE Trans. Inf. Syst. E87-D(7):1774-1781, 2004).

Original languageEnglish (US)
Pages (from-to)199-223
Number of pages25
JournalJournal of Supercomputing
Volume43
Issue number3
DOIs
StatePublished - Mar 2008

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture

Keywords

  • Distributed processing
  • Heterogeneous cluster
  • Parallel processing
  • Scalability analysis

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