On the performance-driven load distribution for heterogeneous computational grids
Journal of Computer and System Sciences
A performance study of grid workflow engines
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Towards decentralized load balancing in a computational grid environment
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
A Compartive Study of Cloud Computing Middleware
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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Job Management Systems (JMSs) efficiently schedule and monitor jobs in parallel and distributed computing environments. Therefore, they are critical for improving the utilization of expensive resources in high-performance computing systems and centers, and an important component of Grid software infrastructure. With many JMSs available commercially and in the public domain, it is difficult to choose an optimum JMS for a given computing environment. In this paper, we present the results of the first empirical study of JMSs reported in the literature. Four commonly used systems, LSF, PBS Pro, Sun Grid Engine/CODINE, and Condor were considered. The study has revealed important strengths and weaknesses of these JMSs under different operational conditions. For example, LSF was shown to exhibit excellent throughput for a wide range of job types and submission rates. Alternatively, CODINE appeared to outperform other systems in terms of the average turn-around time for small jobs, and PBS appeared to excel in terms of turn-around time for relatively larger jobs. Copyright © 2004 John Wiley & Sons, Ltd.