Scheduling in the Grid application development software project

Authors:
Holly Dail;Otto Sievert;Fran Berman;Henri Casanova;Asim YarKhan;Sathish Vadhiyar;Jack Dongarra;Chuang Liu;Lingyun Yang;Dave Angulo;Ian Foster
Affiliations:
San Diego Supercomputer Center, University of California, San Diego;Department of Computer Science and Engineering, University of California, San Diego;San Diego Supercomputer Center, University of California, San Diego and Department of Computer Science and Engineering, University of California, San Diego;San Diego Supercomputer Center, University of California, San Diego and Department of Computer Science and Engineering, University of California, San Diego;Department of Computer Science, University of Tennessee;Department of Computer Science, University of Tennessee;Department of Computer Science, University of Tennessee;Department of Computer Science, The University of Chicago;Department of Computer Science, The University of Chicago;Department of Computer Science, The University of Chicago;Department of Computer Science, The University of Chicago and Mathematics and Computer Science Division, Argonne National Laboratory
Venue:
Grid resource management
Year:
2004

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Abstract

Developing Grid applications is a challenging endeavor that at the moment requires both extensive labor and expertise. The Grid Application Development Software Project (GrADS) provides a system to simplify Grid application development. This system incorporates tools at all stages of the application development and execution cycle. In this chapter we focus on application scheduling, and present the three scheduling approaches developed in GrADS: development of an initial application schedule (launch-time scheduling), modification of the execution platform during execution (rescheduling), and negotiation between multiple applications in the system (metascheduling). These approaches have been developed and evaluated for platforms that consist of distributed networks of shared workstations, and applied to real-world parallel applications.