• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Workshop on Job Scheduling Strategies for Parallel Processing(JSSPP 2004); 20040613; New York,NY(US) >Exploiting Replication and Data Reuse to Efficiently Schedule Data-Intensive Applications on Grids
【24h】

Exploiting Replication and Data Reuse to Efficiently Schedule Data-Intensive Applications on Grids

机译：利用复制和数据重用在网格上有效地调度数据密集型应用程序

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Data-intensive applications executing over a computational grid demand large data transfers. These are costly operations. Therefore, taking them into account is mandatory to achieve efficient scheduling of data-intensive applications on grids. Further, within a heterogeneous and ever changing environment such as a grid, better schedules are typically attained by heuristics that use dynamic information about the grid and the applications. However, this information is often difficult to be accurately obtained. On the other hand, although there are schedulers that attain good performance without requiring dynamic information, they were not designed to take data transfer into account. This paper presents Storage Affinity, a novel scheduling heuristic for bag-of-tasks data-intensive applications running on grid environments. Storage Affinity exploits a data reuse pattern, common on many data-intensive applications, that allows it to take data transfer delays into account and reduce the makespan of the application. Further, it uses a replication strategy that yields efficient schedules without relying upon dynamic information that is difficult to obtain. Our results show that Storage Affinity may attain better performance than the state-of-the-art knowledge-dependent schedulers. This is achieved at the expense of consuming more CPU cycles and network bandwidth.
机译：在计算网格上执行的数据密集型应用程序需要大量数据传输。这些都是昂贵的操作。因此，必须考虑这些因素，以实现网格上数据密集型应用程序的有效调度。此外，在诸如网格之类的异构且不断变化的环境中，通常通过使用关于网格及其应用程序的动态信息的试探法来获得更好的调度。但是，该信息通常难以准确获得。另一方面，尽管有些调度程序可以在不需要动态信息的情况下达到良好的性能，但是它们并不是为了考虑数据传输而设计的。本文介绍了Storage Affinity，这是一种新颖的调度启发式方法，适用于在网格环境中运行的任务包数据密集型应用程序。 Storage Affinity利用了许多数据密集型应用程序中常见的数据重用模式，该模式允许它考虑数据传输延迟并减少应用程序的有效期。此外，它使用一种复制策略，该策略可产生有效的计划，而不必依赖于难以获取的动态信息。我们的结果表明，存储亲和性可能比最新的知识相关调度器具有更好的性能。以消耗更多的CPU周期和网络带宽为代价来实现。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号