Analysis of optimal thread pool size

Author:

Ling Yibei1,Mullen Tracy1,Lin Xiaola2

Affiliation:

1. Telcordia Technologies, 445 South Street, Morristown, NJ

2. Department of Electrical Engineering, Hong Kong University

Abstract

The success of e-commerce, messaging middleware, and other Internet-based applications depends in part on the ability of network servers to respond in a timely and reliable manner to simultaneous service requests. Multithreaded systems, due to their efficient use of system resources and the popularity of shared-memory multi-processor architectures, have become the server implementation of choice. However, creating and destroying a thread is far from free, requiring run-time memory allocation and deallocation. These overheads become especially onerous during periods of high load and can be a major factor behind system slowdowns. A thread-pool architecture addresses this problem by prespawning and then managing a pool of threads. Threads in the pool are reused, so that thread creation and destruction overheads are incurred only once per thread, and not once per request. However, efficient thread management for a given system load highly depends on the thread pool size, which is currently determined heuristically. In this paper, we characterize several system resource costs associated with thread pool size. If the thread pool is too large, and threads go unused, then processing and memory resources are wasted maintaining the thread pool. If the thread pool is too small, then additional threads must be created and destroyed on the fly to handle new requests. We analytically determine the optimal thread pool size to maximize the expected gain of using a thread.

Publisher

Association for Computing Machinery (ACM)

Reference17 articles.

Cited by 28 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

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