Abstract
This paper addresses the dynamic scheduling of moldable jobs with QoS demands (soft-deadlines) in multiclusters. A moldable job can be run on a variable number of resources. Three metrics (over-deadline, makespan and idle-time) are combined with weights to evaluate the scheduling performance. Two levels of performance optimisation are applied in the multicluster. At the multicluster level, a scheduler (which we call MUSCLE) allocates parallel jobs with high packing potential to the same cluster; MUSCLE also takes the jobs’ QoS requirements into account and employs a heuristic to achieve performance balancing across the multicluster. At the single cluster level, an existing workload manager, called TITAN, utilizes a genetic algorithm to further improve the scheduling performance of the jobs allocated by MUSCLE. Extensive experimental studies are conducted to verify the effectiveness of the scheduling mechanism in MUSCLE. The results show that the comprehensive scheduling performance of parallel jobs is significantly improved across the multicluster.
This work is sponsored in part by grants from the NASA AMES Research Center (administrated by USARDSG, contract no. N68171-01-C-9012), the EPSRC (contract no. GR/ R47424/01) and the EPSRC e-Science Core Programme (contract no. GR/S03058/01).
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References
Barreto, M., Avila, R., Navaux, P.: The MultiCluster model to the integrated use of multiple workstation clusters. In: Proc. of the 3rd Workshop on Personal Computerbased Networks of Workstations, pp. 71–80 (2000)
Buyya, R., Baker, M.: Emerging Technologies for Multicluster/Grid Computing. In: Proceedings of the 2001 IEEE International Conference on Cluster Computing (2001)
Cao, J., Kerbyson, D.J., Nudd, G.R.: Performance Evaluation of an Agent-Based Resource Management Infrastructure for Grid Computing. In: Proc. of 1st IEEE/ACM International Symposium on Cluster Computing and the Grid (2001)
Cao, J., Kerbyson, D.J., Papaefstathiou, E., Nudd, G.R.: Performance Modeling of Parallel and Distributed Computing Using PACE. In: Proceedings of 19th IEEE Intl Performance, Computing, and Communications Conference (2000)
Cao, J., Spooner, D.P., Jarvis, S.A., Nudd, G.R.: Grid load balancing using intelligent agents. To appear in Future Generation Computer Systems special issue on Intelligent Grid Environments: Principles and Applications (2004)
He, L., Jarvis, S.A., Spooner, D.P., Nudd, G.R.: Optimising static workload allocation in multiclusters. In: Proceedings of 18th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2004), April 26-30 (2004)
He, X., Sun, X., Laszewski, G.: QoS Guided Min-Min Heuristic for Grid Task Scheduling. Journal of Computer Sci.&Tech., Special Issue on Grid Computing 18(4) (2003)
Lawson, B.G., Smirni, E.: Multiple-queue Backfilling Scheduling with Priorities and Reservations for Parallel Systems. In: 8th Job Scheduling Strategies for Parallel Processing (2002)
Mu’alem, A.W., Feitelson, D.G.: Utilization, predictability, workloads, and user runtime estimates in scheduling the IBM SP2 with backfilling. IEEE Trans. Parallel & Distributed Syst. 12(6), 529–543 (2001)
Nudd, G.R., Kerbyson, D.J., Papaefstathiou, E., Harper, J.S., Perry, S.C., Wilcox, D.V.: PACE: A Toolset for the Performance Prediction of Parallel and Distributed Systems. The Intl Journal of High Performance Computing (1999)
Shmueli, E., Feitelson, D.G.: Backfilling with lookahead to optimize the performance of parallel job scheduling. In: 9th Job Scheduling Strategies for Parallel Processing (2003)
Spooner, D.P., Jarvis, S.A., Cao, J., Saini, S., Nudd, G.R.: Local Grid Scheduling Techniques using Performance Prediction. IEE Proc. Comp. Digit. Tech. 150(2), 87–96 (2003)
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He, L., Jarvis, S.A., Spooner, D.P., Chen, X., Nudd, G.R. (2004). Hybrid Performance-Oriented Scheduling of Moldable Jobs with QoS Demands in Multiclusters and Grids. In: Jin, H., Pan, Y., Xiao, N., Sun, J. (eds) Grid and Cooperative Computing - GCC 2004. GCC 2004. Lecture Notes in Computer Science, vol 3251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30208-7_34
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DOI: https://doi.org/10.1007/978-3-540-30208-7_34
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