By Dan Tsafrir, Yoav Etsion, Dror G. Feitelson (auth.), Dror Feitelson, Eitan Frachtenberg, Larry Rudolph, Uwe Schwiegelshohn (eds.)
This booklet constitutes the completely refereed postproceedings of the eleventh overseas Workshop on task Scheduling ideas for Parallel Processing, JSSPP 2005, held in Cambridge, MA, united states in June 2005 along side the nineteenth ACM foreign convention on Supercomputing (ICS 2005).
The thirteen revised complete learn papers awarded went via rounds of reviewing and development. The papers during this quantity disguise quite a lot of parallel architectures, from dispensed grids, via clusters, to massively-parallel supercomputers. they're equipped in topical sections on modeling and workloads, implementations and deployments, grid scheduling, in addition to assessment and metrics.
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Extra info for Job Scheduling Strategies for Parallel Processing: 11th International Workshop, JSSPP 2005, Cambridge, MA, USA, June 19, 2005, Revised Selected Papers
Pp. 1–10, Springer Verlag, 2001. Lect. Notes Comput. Sci. vol. 2221. 6. A. B. Downey, “A parallel workload model and its implications for processor allocation”. In 6th Intl. Symp. , pp. 112–124, Aug 1997. 7. Y. Etsion and D. Tsafrir, A Short Survey of Commercial Cluster Batch Schedulers. Technical Report 2005-13, Hebrew University, May 2005. 8. D. G. Feitelson, “Experimental analysis of the root causes of performance evaluation results: a backﬁlling case study”. IEEE Trans. Parallel & Distributed Syst.
The original estimate distribution of the traces (solid lines) vs. the output of the vanilla model, when used with four diﬀerent seeds. Output is less successful for traces with unique features. SDSC-106 100 80 CDF [%] CTC KTH4H BLUE seed0 seed1 seed2 seed3 orig 60 40 20 5m 15m 30m 1h 2h 4h 8h 18h 36h 5m 15m 30m 1h 2h 4h 8h 18h 36h 1m 5m 15m 30m 1h 2h 4h 8h 18h 36h 1m 5m 15m 30m 1h 2h 4h 8h 18h 36h 1m 1m 0 estimate Fig. 15. Output of the model under the “improved” setting which provides minimal information identifying the unique features The results of the improved setting are shown in Fig.
The f -model: upon receiving a job’s runtime R, uniformly chooses an estimate from the closed range [R, R ·(f + 1)]. In accordance with , six values of f were chosen: 0 (complete accuracy), 1, 3, 10, 100, and 300. – The feit-model: targets accuracy (suggested by Mu’alem and Feitelson  and explained in the introduction). – The vanl-model: the vanilla setting of the model developed in this paper (deﬁned above). – The impr-model: the improved setting of our model, supplying it with some additional information (deﬁned above).
Job Scheduling Strategies for Parallel Processing: 11th International Workshop, JSSPP 2005, Cambridge, MA, USA, June 19, 2005, Revised Selected Papers by Dan Tsafrir, Yoav Etsion, Dror G. Feitelson (auth.), Dror Feitelson, Eitan Frachtenberg, Larry Rudolph, Uwe Schwiegelshohn (eds.)