An Adaptive Job Scheduler for Timeshared Parallel Machines

Computational power, at least at the high end, can be thought of as a utility, similar to electricity or water. To make this metaphor work requires a sophisticated ``power distribution'' infrastructure. The ``Grid'', popularized by the Globus project, is an example of such an infrastructure. To function efficiently, the producers of compute Power -- the parallel servers -- must be able to reorganize their jobs dynamically so as to respond to demands for computational power quickly, and maximize their utility. We are developing a framework, called faucets, that aims at facilitating this process. This paper focuses on a system at the heart of this framework: an adaptive manager for timeshared parallel machines that can shrink and expand its jobs to a variable number of processors dynamically. This manager has been implemented for workstation clusters. The paper describes the faucets framework, the design of the adaptive job manager, and preliminary performance data.

Laxmikant V. Kale and Sameer Kumar and Jayant DeSouza. "An Adaptive Job 
Scheduler for Timeshared Parallel Machines". Parallel Programming Laboratory, 
Department of Computer Science, University of Illinois at Urbana-Champaign, 
September, 2000.

@techreport{shrink-ipdps,
 key="ShrinkINTL00",
 Title= "An Adaptive Job Scheduler for Timeshared Parallel Machines",
 Author = "Laxmikant V. Kal\'e and Sameer Kumar and Jayant DeSouza",
 Institution = "Parallel Programming Laboratory, Department of
          Computer Science, University of Illinois at
          Urbana-Champaign",
 number = "00-02",
 year = "2000",
 month = "Sep"
}