【24h】

Job Scheduling Optimization of High Performance Computing in Biological Gene Sequencing Based on Workload Analysis

机译:基于工作量分析的生物基因测序中高性能计算的作业调度优化

获取原文
获取原文并翻译 | 示例

摘要

Mining job scheduling features based on extraction and analysis of workload trace in high performance computing clusters can be used to optimize scheduling strategy and enhance system performance. Based on detailed analysis of workload trace from a gene sequencing high performance computing system, this paper proposes a multi-queue backfilling scheduling algorithm, which is based on traditional backfilling scheduling. While optimizing for memory resource demands, this algorithm provides queue level load balancing to deal with the innate load imbalance characteristics of high performance systems. Experimental results based on practical gene sequencing workload trace clearly demonstrate that compared with traditional scheduling algorithms, the algorithm proposed in this paper is a good strategy to reduce the job waiting time and improve resource utilization.
机译:基于高性能计算集群中基于工作负载跟踪的提取和分析的挖掘作业调度功能可用于优化调度策略并增强系统性能。在对基因测序高性能计算系统的工作量跟踪进行详细分析的基础上,提出了一种基于传统回填调度的多队列回填调度算法。在优化内存资源需求的同时,该算法提供了队列级别的负载平衡,以应对高性能系统固有的负载不平衡特性。基于实际基因测序工作量跟踪的实验结果清楚地表明,与传统的调度算法相比,本文提出的算法是减少作业等待时间,提高资源利用率的良好策略。

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