Performance prediction and its use in parallel and distributed computing systems

Stephen A. Jarvis, Daniel P. Spooner, Helene N. Lim Choi Keung, Junwei Cao, Subhash Saini, Graham R. Nudd

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)

Abstract

Performance prediction is set to play a significant role in supportive middleware that is designed to manage workload on parallel and distributed computing systems. This middleware underpins the discovery of available resources, the identification of a task's requirements and the match-making, scheduling and staging that follow. This paper documents two prediction-based middleware services that address the implications of executing a particular workload on a given set of resources. These services are based on an established performance prediction system that is employed at both the local (intra-domain) and global (multi-domain) levels to provide dynamic workload steering. These additional facilities bring about significant performance improvements, the details of which are presented with regard to system- and user-level qualities of service. The middleware has been designed for the management of resources and distributed workload across multiple administrative boundaries, a requirement that is of central importance to grid computing.

Original languageEnglish
Pages (from-to)745-754
Number of pages10
JournalFuture Generation Computer Systems
Volume22
Issue number7
DOIs
Publication statusPublished - Aug 2006

Bibliographical note

Funding Information:
Sponsored in part by grants from the NASA AMES Research Center (USARDSG N68171-01-C-9012), the EPSRC (GR/R47424/01) and the EPSRC e-Science Core Programme (GR/S03058/01).

Keywords

  • Grid computing
  • Performance prediction
  • Resource management

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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