An Evaluation of Parallel Job Scheduling for ASCI Blue-Pacific
In this paper we analyze the behavior of a gang-scheduling strategy that we are developing for the ASCI Blue-Pacific machines. Using actual job logs for one of the ASCI machines we generate a statistical model of the current workload with hyper Erlang distributions. We then vary the parameters of those distributions to generate various workloads, representative of different operating points of the machine. Through simulation we obtain performance parameters for three different scheduling strategies: (i) first-come first-serve, (ii) gang-scheduling, and (iii) backfilling. Our results show that backfilling, can be very effective for the common operating points in the 60-70% utilization range. However, for higher utilization rates, time-sharing techniques such as gang-scheduling offer much better performance.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE Office of Defense Programs (DP) (US)
- DOE Contract Number:
- W-7405-Eng-48
- OSTI ID:
- 790820
- Report Number(s):
- UCRL-JC-136397; TRN: US200206%%81
- Resource Relation:
- Conference: Supercomputing 1999, Portland, OR (US), 11/14/1999--11/19/1999; Other Information: PBD: 9 Nov 1999
- Country of Publication:
- United States
- Language:
- English
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