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Titlebook: Job Scheduling Strategies for Parallel Processing; 10th International W Dror G. Feitelson,Larry Rudolph,Uwe Schwiegelshohn Conference proce

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发表于 2025-3-21 16:56:06 | 显示全部楼层 |阅读模式
书目名称Job Scheduling Strategies for Parallel Processing
副标题10th International W
编辑Dror G. Feitelson,Larry Rudolph,Uwe Schwiegelshohn
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Job Scheduling Strategies for Parallel Processing; 10th International W Dror G. Feitelson,Larry Rudolph,Uwe Schwiegelshohn Conference proce
描述This volume contains the papers presented at the 10th Anniversary Workshop on Job Scheduling Strategies for Parallel Processing. The workshop was held in New York City, on June 13, 2004, at Columbia University, in conjunction with the SIGMETRICS 2004 conference. Although it is a workshop, the papers were conference-reviewed, with the full versions being read and evaluated by at least five and usually seven members of the Program Committee. We refer to it as a workshop because of the very fast turnaround time, the intimate nature of the actual presentations, and the ability of the authors to revise their papers after getting feedback from workshop attendees. On the other hand, it was actually a conference in that the papers were accepted solely on their merits as decided upon by the Program Committee. We would like to thank the Program Committee members, Su-Hui Chiang, Walfredo Cirne, Allen Downey, Eitan Frachtenberg, Wolfgang Gentzsch, Allan Gottlieb, Moe Jette, Richard Lagerstrom, Virginia Lo, Reagan Moore, Bill Nitzberg, Mark Squillante, and John Towns, for an excellent job. Thanks are also due to the authors for their submissions, presentations, and final revisions for this volu
出版日期Conference proceedings 2005
关键词Scheduling; Supercomputer; algorithm; algorithms; distributed systems; load balancing; memory management; m
版次1
doihttps://doi.org/10.1007/b107134
isbn_softcover978-3-540-25330-3
isbn_ebook978-3-540-31795-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2005
The information of publication is updating

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发表于 2025-3-21 20:13:24 | 显示全部楼层
Scheduling on the Top 50 Machines,ling on these machines. As this statistic is interesting for researchers and system designers, this paper gives an overview and survey on scheduling relevant information for the first 50 entries in the TOP500 list.
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Parallel Computer Workload Modeling with Markov Chains,on the workload that is served on the parallel machine, a representative workload model is required. Common approaches such as using a probability distribution model can capture the static feature of real workloads, but they do not consider the temporal relation in the traces. In this paper, a workl
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Enhancements to the Decision Process of the Self-Tuning dynP Scheduler, time. This allows to react on changing characteristics of the waiting jobs. In this paper we present enhancements to the decision process of the self-tuning . scheduler and evaluate their impact on the performance: (i) While doing a self-tuning step a performance metric is needed for ranking the sc
发表于 2025-3-22 10:45:39 | 显示全部楼层
Reconfigurable Gang Scheduling Algorithm,this problem is an algorithm that is capable of dynamically changing its form (configuration) into a more appropriate one, according to environment variations and user requirements. In this paper, we propose, implement and analyze the performance of a Reconfigurable Gang Scheduling Algorithm (RGSA)
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Multi-toroidal Interconnects: Using Additional Communication Links to Improve Utilization of Parallmitted to a three-dimensional toroidal machine typically requires an isolated, contiguous, rectangular partition connected as a mesh or a torus. Such partitioning leads to fragmentation and thus reduces resource utilization of the machines. In particular, toroidal partitions often require allocation
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Workload Characteristics of a Multi-cluster Supercomputer,that we characterize include system utilization, job arrival rate and interarrival time, job cancellation rate, job size (degree of parallelism), job runtime, memory usage, and user/group behavior. Correlations between metrics (job runtime and memory usage, requested and actual runtime, etc) are ide
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