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.
Bibliographical noteFunding 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).
- Grid computing
- Performance prediction
- Resource management
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Networks and Communications