Job Scheduling Strategies for Parallel Processing

This volume contains the papers presented at the sixth workshop on Job Sched- ing Strategies for Parallel Processing, which was held in conjunction with the IPDPS 2000 Conference in Cancun, Mexico, on 1 May 2000. The papers have been through a complete refereeing process, with the full version being read and evaluated by ?ve to seven members of the program committee. We would like to take this opportunity to thank the program committee, Andrea Arpaci-Dusseau, Fran Berman, Steve Chapin, Allen Downey, Allan Gottlieb, Atsushi Hori, Phil Krueger, Richard Lagerstrom, Virginia Lo, Reagan Moore, Bill Nitzberg, Uwe Schwiegelshohn, and Mark Squillante, 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 S- ence and the Computer Science Institute at the Hebrew University for the use of their facilities in the preparation of these proceedings. This was the sixth annual workshop in this series, which re?ects the continued interest in this ?eld. The previous ?ve were held in conjunction with IPPS 95 through IPPS/SPDP 99. Their proceedings are available from Springer-Verlag as volumes 949, 1162, 1291, 1459, and 1659 of the Lecture Notes in Computer Science series. The last two are also available on-line from Springer LINK.

Includes supplementary material: sn.pub/extras

Inhalt
Effect of Job Size Characteristics on Job Scheduling Performance.- Improving Parallel Job Scheduling Using Runtime Measurements.- Valuation of Ultra-scale Computing Systems.- System Utilization Benchmark on the Cray T3E and IBM SP.- A Critique of ESP.- Resource Allocation Schemes for Gang Scheduling.- A Tool to Schedule Parallel Applications on Multiprocessors: The NANOS CPU Manager.- Time-Sharing Parallel Jobs in the Presence of Multiple Resource Requirements.- The Performance Impact of Advance Reservation Meta-scheduling.- The Influence of the Structure and Sizes of Jobs on the Performance of Co-allocation.- Load Balancing for Minimizing Execution Time of a Target Job on a Network of Heterogeneous Workstations.- Adaptive Selection of Partition Size for Supercomputer Requests.