Coscheduling in Clusters: Is It a Viable Alternative?
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
What is worth learning from parallel workloads?: a user and session based analysis
Proceedings of the 19th annual international conference on Supercomputing
A comprehensive performance and energy consumption analysis of scheduling alternatives in clusters
The Journal of Supercomputing
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Characteristics of the workload on ASCI Blue-Pacific, a 336-node IBM SP2 SMP-cluster machine at Lawrence Livermore National Laboratory (LLNL), are discussed in this paper. It is shown that majority of jobs have very short inter-arrival time and execution time with relatively long waiting delay. It is also shown that the node and memory demands of jobs are surprisingly small. This findings strongly encourage the use of a scheduling technique which combines both space- and time-sharing to improve system performance. Contrary to our expectations, there is little correlation between job's execution time and resource demands. Although large jobs constitute a relatively small fraction of total job population, they consume most of the resources.