Job Scheduling Strategies for Parallel Processing

This volume contains the papers presented at the 9th workshopon Job Sched- ing Strategies for Parallel Processing, which was held in conjunction with HPDC12 and GGF8 in Seattle, Washington, on June 24, 2003. The papers went through a complete review process, with the full version being read and eva- ated by ?ve to seven members of the program committee. We would like to take this opportunity to thank the program committee, Su-Hui Chiang, Walfredo Cirne, Allen Downey, Wolfgang Gentzsch, Allan Gottlieb, Moe Jette, Richard Lagerstrom, Virginia Lo, Cathy McCann, Reagan Moore, Bill Nitzberg, Mark Squillante, and John Towns, for an excellent job. Thanks are also due to the authors for their submissions, presentations, and ?nal revisions for this volume. Finally, we would like to thank the MIT Laboratory for Computer Science and the School of Computer Science and Engineering at the Hebrew University for the use of their facilities in the preparation of these proceedings. This year we had papers on three main topics. The ?rst was continued work on conventional parallel systems, including infrastructure and scheduling al- rithms. Notable extensions include the considerationof I/O and QoSissues. The secondmajortheme wasscheduling inthe contextofgridcomputing, whichc- tinues to be an area of much activity and rapid progress.The third area was the methodological aspects of evaluating the performance of parallel job scheduling.

Includes supplementary material: sn.pub/extras

Scheduling in HPC Resource Management Systems: Queuing vs. Planning.- TrellisDAG: A System for Structured DAG Scheduling.- SLURM: Simple Linux Utility for Resource Management.- OurGrid: An Approach to Easily Assemble Grids with Equitable Resource Sharing.- Scheduling of Parallel Jobs in a Heterogeneous Multi-site Environment.- A Measurement-Based Simulation Study of Processor Co-allocation in Multicluster Systems.- Grids for Enterprise Applications.- Performance Estimation for Scheduling on Shared Networks.- Scaling of Workload Traces.- Gang Scheduling Extensions for I/O Intensive Workloads.- Parallel Job Scheduling under Dynamic Workloads.- Backfilling with Lookahead to Optimize the Performance of Parallel Job Scheduling.- QoPS: A QoS Based Scheme for Parallel Job Scheduling.