A Jobs Allocation Strategy for Multiple DRBL Diskless Linux Clusters with Condor Schedulers

Chao-Tung Yang, Ping-I Chen, Sung-Yi Chen, Hao-Yu Tung
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引用次数: 2

Abstract

In this paper, we construct four DRBL-based diskless Linux PC clusters and install Globus Toolkit and Condor scheduler on the master node of each cluster. All diskless clusters can be merged into a powerful computing environment. To utilize the computing power, we propose a jobs allocation strategy for application execution. We use HPL to conduct some performance evaluations and analyze those data to form a formula for jobs allocation. The information server will calculate the value of computing power based on our formula and find the most appropriate cluster to execute the job. It can make our large computing environment that can execute the jobs in a more efficient way
基于Condor调度器的多DRBL无磁盘Linux集群作业分配策略
本文构建了4个基于drbl的无磁盘Linux PC集群,并在每个集群的主节点上安装了Globus Toolkit和Condor调度程序。所有无磁盘集群都可以合并到一个强大的计算环境中。为了充分利用计算能力,我们提出了一种应用程序执行任务分配策略。我们使用HPL进行一些绩效评估,并对这些数据进行分析,形成工作分配公式。信息服务器将根据我们的公式计算计算能力的值,并找到最合适的集群来执行任务。它可以使我们的大型计算环境以更有效的方式执行任务
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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