Performance prediction and its use in parallel and distributed computing systems

  • Authors:

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

  • Affiliations:

  • Department of Computer Science, University of Warwick, Warwick, UK;Department of Computer Science, University of Warwick, Warwick, UK;Department of Computer Science, University of Warwick, Warwick, UK;Center for Space Research, Massachusetts Institute of Technology, Cambridge, MA;NASA Ames Research Center, Moffett Field, CA;Department of Computer Science, University of Warwick, Warwick, UK

  • Venue:
  • Future Generation Computer Systems - Systems performance analysis and evaluation
  • Year:
  • 2006

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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 matchmaking, 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.