The impact of job memory requirements on gang-scheduling performance

Author:

Setia Sanjeev1,Squillante Mark S.2,Naik Vijay K.2

Affiliation:

1. Computer Science Department, George Mason University, Fairfax, VA

2. IBM Thomas J. Watson Research Center, P.O. Box 704, Yorktown Heights, NY

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.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC;Business Intelligence;2016

2. Practical Resource Management in Power-Constrained, High Performance Computing;Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing;2015-06-15

3. QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC;International Journal of Grid and High Performance Computing;2014-10

4. Dynamic Fractional Resource Scheduling versus Batch Scheduling;IEEE Transactions on Parallel and Distributed Systems;2012-03

5. Service control with the preemptive parallel job scheduler Scojo-PECT;Cluster Computing;2010-10-26

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