Scheduling arbitrary number of malleable tasks on multiprocessor systems

Author:

Barketau M.S.,Kovalyov M.Y.,Węglarz J.,Machowiak M.

Abstract

Abstract The problem of scheduling n tasks in a multiprocessor system with m processors to minimize the makespan is studied. Tasks are malleable, which means that a task can be executed by several processors at a time, its processing speed depends on the number of allocated processors, and a set of processors allocated to the same task can change over time. The processing speed of a task is a strictly increasing function of the number of processors allocated to this task. The earlier studies considered the case n ≤ m. This paper presents results for arbitrary n and m including characterizations of a feasible domain and an optimal solution, polynomial time algorithms for strictly increasing convex and concave processing speed functions, and a combinatorial exponential algorithm for arbitrary strictly increasing functions.

Publisher

Walter de Gruyter GmbH

Subject

Artificial Intelligence,Computer Networks and Communications,General Engineering,Information Systems,Atomic and Molecular Physics, and Optics

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient approximation algorithms for scheduling moldable tasks;European Journal of Operational Research;2023-10

2. An Improved Approximation for Scheduling Malleable Tasks with Precedence Constraints via Iterative Method;IEEE Transactions on Parallel and Distributed Systems;2018-09-01

3. Optimal workforce assignment to operations of a paced assembly line;European Journal of Operational Research;2018-01

4. Discrete-continuous project scheduling with preemptable activities;Bulletin of the Polish Academy of Sciences Technical Sciences;2016-06-01

5. A multi-level method of support for management of product flow through supply chains;Bulletin of the Polish Academy of Sciences Technical Sciences;2015-12-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3