Robust scalability analysis and SPM case studies

Document Type

Article

Publication Date

3-1-2008

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). © 2007 Springer Science+Business Media, LLC.

Identifier

38349064853 (Scopus)

Publication Title

Journal of Supercomputing

External Full Text Location

https://doi.org/10.1007/s11227-007-0140-6

e-ISSN

15730484

ISSN

09208542

First Page

199

Last Page

223

Issue

3

Volume

43

Grant

CNS-0435250

Fund Ref

National Science Foundation

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