【24h】

A Scalability Metric for Algorithm-Machine on NOW and MPP

机译:基于NOW和MPP的算法机器的可伸缩性度量

获取原文

摘要

Along with the rapid development of parallel processing technology and the poprlarity of NOW. the scalability of parallel algorithm-machine combinations. which measures the capacity of a parallel algorithm to effectively utilize an increasing number of a parallel algorithm to effectively utilize an increasing number of processors, becomes more and more important. In this paper, we present a new metric, called time_scale metric, to measure and evaluate the scalability of parallel algorithms and machines, and extend it to fit the characteristics of NOW. The experimental results show that the time-scale metric is a practical and accurate method to evaluate the scalability of parallel algorithms on MPP and NOW.
机译:随着并行处理技术的飞速发展和NOW的普及。并行算法-机器组合的可伸缩性。测量并行算法有效利用越来越多的并行算法以有效利用数量越来越多的处理器的能力变得越来越重要。在本文中,我们提出了一种新的度量标准,称为time_scale度量标准,用于度量和评估并行算法和机器的可伸缩性,并对其进行扩展以适合NOW的特性。实验结果表明,时标是一种评估MPP和NOW并行算法可扩展性的实用而准确的方法。

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