利用排队系统预测并行计算模型的性能

Chao Shen, W. Tong, Samina Kausar
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引用次数: 8

摘要

计算模型为云计算提供了并行和分布式算法。评估并行计算模型的性能以实现有效的资源调度的能力是至关重要的。目前的性能预测技术主要是基于分析和模拟。并行计算模型的特性直接导致了数学模型的多样性。如果没有通用的预测模型,就很难在几个关键方面比较相当不同的并行计算模型,包括计算能力、资源配置、可伸缩性、容错性等。在本文中,我们设计了一个用排队系统来预测性能的数学模型。我们制作了各种计算模型作为屏蔽分集的服务系统。利用作业等待时间和作业执行时间可以准确估计作业的性能。还可以考虑计算节点的异构性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting the Performance of Parallel Computing Models Using Queuing System
Computing models provide the parallel and distributed algorithms for cloud. The ability to estimate the performance of parallel computing models for efficient resource scheduling is critical. Current techniques for predicting the performance are mostly based on analyzing and simulating. The behavior of parallel computing model directly leads to the diversity of mathematical model. Without a general prediction model, it is very hard to compare fairly different parallel computing models in several critical aspects, including computing capacity, resource configuration, scalability, fault tolerance and so on. In this paper, we design a mathematical model for predicting the performance by using queuing system. We make various computing models as a service system for shielding the diversity. The performance can be accurately estimated with the job waiting time and the job performing time. The heterogeneity of computing nodes may also be considered.
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