A Proposal of Static Job Scheduling Algorithm Considering CPU Core Utilization for User-PC Computing System

Ariel Kamoyedji, N. Funabiki, Hein Htet, M. Kuribayashi
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引用次数: 4

Abstract

The User-PC computing system (UPC) has been devised to provide a very low-cost distributed computing platform to members of a group, using idling resources of their personal computers (PCs). Based on the master-worker model, the master PC accepts jobs from users and assigns them to available worker PCs. Unfortunately, an efficient job assignment method has not been implemented yet. In this paper, we propose a static job scheduling algorithm considering the CPU core utilization, for the UPC system. Given a set of independent jobs, this two-stage heuristic algorithm finds an assigned worker for each job in order to minimize the makespan. To efficiently utilize CPU cores in worker PCs, the first stage groups workers and jobs into several classes according to the number of available cores or threads. It then greedily sets up job-worker assignments in each class independently. The second stage improves the assignments with a local search method by randomly moving job-worker assignments between different classes. For evaluation, we conducted experiments using six worker PCs and up to 27 jobs. Our algorithm could reduce the makespan by up to 60% compared to three baseline scheduling algorithms. However, its performance gradually decreases as the number of jobs significantly increases.
一种考虑CPU核心利用率的用户pc计算系统静态作业调度算法
用户- pc计算系统(UPC)的设计目的是利用个人计算机(pc)的空闲资源,为小组成员提供一个非常低成本的分布式计算平台。基于主-worker模型,主PC接受来自用户的作业,并将它们分配给可用的worker PC。不幸的是,一种有效的工作分配方法尚未实现。本文针对UPC系统,提出了一种考虑CPU内核利用率的静态作业调度算法。给定一组独立的作业,这个两阶段启发式算法为每个作业找到一个分配的工人,以最小化完工时间。为了有效地利用工作pc中的CPU内核,第一阶段根据可用内核或线程的数量将工作和作业分成几个类。然后,它贪婪地在每个类中独立地设置job-worker分配。第二阶段通过在不同类之间随机移动job-worker分配,使用局部搜索方法改进分配。为了进行评估,我们使用6台工人pc和多达27个工作岗位进行了实验。与三种基线调度算法相比,我们的算法可以将最大完工时间减少60%。但是,随着工作数量的显著增加,其性能逐渐下降。
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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