William M. Jones, Louis W. Pang, W. Ligon, D. Stanzione
{"title":"Bandwidth-aware co-allocating meta-schedulers for mini-grid architectures","authors":"William M. Jones, Louis W. Pang, W. Ligon, D. Stanzione","doi":"10.1109/CLUSTR.2004.1392600","DOIUrl":null,"url":null,"abstract":"The interaction of simultaneously co-allocated jobs can often create contention in the network infrastructure of a dedicated computational grid. This contention can lead to degraded job run-time performance. We present several bandwidth-aware co-allocating meta-schedulers. These schedulers take into account inter-cluster network utilization as a means by which to mitigate this impact. We make use of a bandwidth-centric parallel job communication model that captures the time-varying utilization of shared inter-cluster network resources. By doing so, we are able to evaluate the performance of grid scheduling algorithms that focus not only on node resource allocation, but also on shared inter-cluster network bandwidth.","PeriodicalId":123512,"journal":{"name":"2004 IEEE International Conference on Cluster Computing (IEEE Cat. No.04EX935)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference on Cluster Computing (IEEE Cat. No.04EX935)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLUSTR.2004.1392600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
The interaction of simultaneously co-allocated jobs can often create contention in the network infrastructure of a dedicated computational grid. This contention can lead to degraded job run-time performance. We present several bandwidth-aware co-allocating meta-schedulers. These schedulers take into account inter-cluster network utilization as a means by which to mitigate this impact. We make use of a bandwidth-centric parallel job communication model that captures the time-varying utilization of shared inter-cluster network resources. By doing so, we are able to evaluate the performance of grid scheduling algorithms that focus not only on node resource allocation, but also on shared inter-cluster network bandwidth.