A decoupled scheduling approach for the GrADS program development environment

• Published in: Proceedings of the 2002 ACM/IEEE conference on Supercomputing pp. 1 - 14
• Main Authors: Dail, Holly, Casanova, Henri, Berman, Fran
• Format: Conference Proceeding
• Language: English
• Published: Los Alamitos, CA, USA IEEE Computer Society Press 16-11-2002
• Series: ACM Conferences
• Subjects: Computing methodologies > Artificial intelligence > Planning and scheduling; Software and its engineering > Software organization and properties > Contextual software domains > Operating systems > Process management > Scheduling; Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Scheduling algorithms; Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms > Scheduling algorithms; Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning > Sequential decision making
• ISBN: 076951524X; 9780769515243
• DOI: 10.5555/762761.762795

Program development environments are instrumental in providing users with easy and efficient access to parallel computing platforms. While a number of such environments have been widely accepted and used for traditional HPC systems, there are currently no widely used environments for Grid programming. The goal of the Grid Application Development Software (GrADS) project is to develop a coordinated set of tools, libraries and run-time execution facilities for Grid program development.In this paper, we describe a Grid scheduler component that is integrated as part of the GrADS software system. Traditionally, application-level schedulers (e.g. AppLeS) have been tightly integrated with the application itself and were not easily applied to other applications. Our design is generic: we decouple the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platform-specific (e.g. collection of resource information) components used by the search procedure. We provide experimental validation of our approach for two representative regular, iterative parallel programs in a variety of real-world Grid testbeds. Our scheduler consistently outperforms static and user-driven scheduling methods.