Combining Workstations and Supercomputers to Support Grid Applications: The Parallel Tomography Experience

Shava Smallen, Walfredo Cirne, Jaime Frey, Fran Berman, Rich Wolski, Mei-Hui Su, Carl Kesselman, Steve Young and Mark Ellisman
CS2000-0642
January 7, 2000

Computational Grids are becoming an increasingly important and powerful platform for the execution of large-scale, resource-intensive applications. However, it remains a challenge for applications to tap the potential of Grid resources in order to achieve performance. In this paper, we illustrate how applications can leverage Grids to achieve performance through coallocation. We describe our experiences developing a scheduling strategy for a real-life parallel tomography application targeted to Grids which contain both workstations and parallel supercomputers. Our strategy uses dynamic information exported by a supercomputer's batch scheduler to simultaneously schedule on workstations and immediately available supercomputer nodes. This strategy is of great practical interest because it combines resources available to the typical research lab: time-shared workstations and CPU time in remote space-shared supercomputers. We show that this strategy improves the performance of the parallel tomography application compared to traditional scheduling strategies, which target the application to either type of resource alone.


How to view this document


The authors of these documents have submitted their reports to this technical report series for the purpose of non-commercial dissemination of scientific work. The reports are copyrighted by the authors, and their existence in electronic format does not imply that the authors have relinquished any rights. You may copy a report for scholarly, non-commercial purposes, such as research or instruction, provided that you agree to respect the author's copyright. For information concerning the use of this document for other than research or instructional purposes, contact the authors. Other information concerning this technical report series can be obtained from the Computer Science and Engineering Department at the University of California at San Diego, techreports@cs.ucsd.edu.


[ Search ]


NCSTRL
This server operates at UCSD Computer Science and Engineering.
Send email to webmaster@cs.ucsd.edu