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| Content Provider | ACM Digital Library |
|---|---|
| Author | Squillante, Mark S. Setia, Sanjeev Naik, Vijay K. |
| Abstract | Almost all previous research on gang-scheduling has ignored the impact of real job memory requirements on the performance of the policy. This is despite the fact that on parallel supercomputers, because of the problems associated with demand paging, executing jobs are typically allocated enough memory so that their entire address space is memory-resident. In this paper, we examine the impact of job memory requirements on the performance of gang-scheduling policies. We first present an analysis of the memory-usage characteristics of jobs in the production workload on the Cray T3E at the San Diego Supercomputer Center. We also characterize the memory usage of some of the applications that form part of the workload on the LLNL ASCI supercomputer. Next, we examine the issue of long-term scheduling on MPPs, i.e., we study policies for deciding which jobs among a set of competing jobs should be allocated memory and thus should be allowed to execute on the processors of the system. Using trace-driven simulation, we evaluate the impact of using different long-term scheduling policies on the overall performance of Distributed Hierarchical Control (DHC), a gang-scheduling policy that has been studied extensively in the research literature. |
| Starting Page | 30 |
| Ending Page | 39 |
| Page Count | 10 |
| File Format | |
| ISSN | 01635999 |
| DOI | 10.1145/309746.309751 |
| Journal | ACM SIGMETRICS Performance Evaluation Review (PERV) |
| Volume Number | 26 |
| Issue Number | 4 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-01-10 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications Hardware and Architecture Software |
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