Job Scheduling Strategies for Parallel Processing: 13th International Workshop, JSSPP 2007, Seattle, WA, USA, June 17, 2007, Revised Papers
th Thisvolumecontainsthepaperspresentedatthe13 workshoponJobSched- ing Strategies for Parallel Processing. The workshop was held in Seattle, WA, USA, on June 17, 2007, in conjunction with ICS 2007. All submitted papers went through a complete review process, with the full versionbeingreadandevaluatedbyanaverageof?vereviewers.Wewouldliketo thanktheProgramCommittee membersandadditionalrefereesfortheirwilli- ness to participate in this e?ort and their excellent, detailed reviews: Nazareno Andrade, Su-Hui Chiang, Walfredo Cirne, Alvaro Coelho, Lauro Costa, Dror Feitelson, Allan Gottlieb, Andrew Grimshaw, Moe Jette, Richard Lagerstrom, Virginia Lo, Reagan Moore, Bill Nitzberg, Mark Squillante, John Towns, Jon Weissman, and Ramin Yahyapour. The accepted workshop papers in recent years show a departure from the supercomputer-centric viewpoint of parallel job scheduling. On the one hand, the ?eld of supercomputer scheduling is showing some signs of maturity, exh- ited in many widely accepted practices for job scheduling. On the other hand, many nontraditionalhigh-performancecomputing andparallelenvironments are emerging as viable solutions to many users and uses that cannot or need not - cess a traditional supercomputer, such as Grids, Web services, and commodity parallelcomputers.With the growingubiquity ofthese technologies, the requi- ment to schedule parallel jobs well on these various architectures also grows.
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New Challenges of Parallel Job Scheduling
GroupWise Performance Evaluation of Processor Coallocation in Multicluster Systems
Enhancing an Open Source Resource Manager with MulticoreMultithreaded Support
A Job Selfscheduling Policy for HPC Infrastructures
Queue Bounds Estimation from Time Series
Impact of Reservations on Production Job Scheduling
Prospects of Collaboration between Compute Providers by Means of Job Interchange
An Advance ReservationBased Grid Coallocation Framework for Distributed Computing and Network Resources
A Selfoptimized Job Scheduler for Heterogeneous Server Clusters
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advance reservation aﬀect aﬃnity algorithm allocation applications architectures AWRT backﬁlling binomial method cluster co-allocation computational resources conﬁdence conﬁgurations cores deﬁned diﬀerent diﬃcult Distributed Computing distribution eﬀect eﬃciently environment evaluation execution expansion factor FCFS Feitelson ﬁle ﬁnd ﬁt ﬂags Frachtenberg global scheduling Grid Computing Grid scheduling GridARS Heidelberg Heidelberg 2005 heterogeneous Hyperthreading implicit feedback improvement job pool job stream job submission job wait job’s JSSPP LNCS load LoadLeveler machine memory meta-scheduler metrics multi-core nodes number of processors oﬀered parallel computers parallel job scheduling partitioning performance predictions predictor QBETS quantile queue delay queue wait requirements reservation process resource capacity resource estimation resource management resource schedulers Rudolph running jobs runtime scenario scheduling policies scheduling system Schwiegelshohn SDSC server signiﬁcant simulation slowdown SLURM sockets speciﬁc Springer submitted jobs supercomputer TeraGrid users utilization Web Services widest component workload WSRF