{"title":"Comparison of garbage collectors in Java programming language","authors":"H. Grgic, B. Mihaljević, Aleksander Radovan","doi":"10.23919/MIPRO.2018.8400277","DOIUrl":null,"url":null,"abstract":"Considering the need for continuous and uninterrupted service of modern software applications, it is valuable to analyze how garbage collection (GC) algorithms are handling memory challenges. Widely adopted general-purpose programming languages, like Java, represent an inevitable foundation for many modern application developments. In Java Platform, Standard Edition, and accompanying Java Virtual Machine (JVM), several GCs could be used. In the latest version 9.0.1 of Java SE Development Kit (JDK) default GC was changed to Garbage-First (G1) GC, now becoming widely adopted in addition to previously used Parallel GC and Concurrent Mark & Sweep (CMS) GC. Since GC is a vital part of the JVM, changes and upgrades to its implementation, which reflect upon performance results, are properties worth exploring. Using benchmarks to create non-trivial memory pressures, and with extensive data monitoring, this paper analyzes insights gathered about critical performance factors across several GC algorithms. With the evaluation of benchmark elements, such as object allocations from young area to old area and the duration of the collection time, it was possible to compare GC behavior and assess the overall memory management. This paper presents our preliminary research performed in an academic environment on several benchmark cases and our conclusion about it.","PeriodicalId":431110,"journal":{"name":"2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MIPRO.2018.8400277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Considering the need for continuous and uninterrupted service of modern software applications, it is valuable to analyze how garbage collection (GC) algorithms are handling memory challenges. Widely adopted general-purpose programming languages, like Java, represent an inevitable foundation for many modern application developments. In Java Platform, Standard Edition, and accompanying Java Virtual Machine (JVM), several GCs could be used. In the latest version 9.0.1 of Java SE Development Kit (JDK) default GC was changed to Garbage-First (G1) GC, now becoming widely adopted in addition to previously used Parallel GC and Concurrent Mark & Sweep (CMS) GC. Since GC is a vital part of the JVM, changes and upgrades to its implementation, which reflect upon performance results, are properties worth exploring. Using benchmarks to create non-trivial memory pressures, and with extensive data monitoring, this paper analyzes insights gathered about critical performance factors across several GC algorithms. With the evaluation of benchmark elements, such as object allocations from young area to old area and the duration of the collection time, it was possible to compare GC behavior and assess the overall memory management. This paper presents our preliminary research performed in an academic environment on several benchmark cases and our conclusion about it.
考虑到现代软件应用程序对连续和不间断服务的需求,分析垃圾收集(GC)算法如何处理内存挑战是有价值的。广泛采用的通用编程语言,如Java,代表了许多现代应用程序开发的不可避免的基础。在Java平台、标准版和附带的Java虚拟机(JVM)中,可以使用几种gc。在Java SE Development Kit (JDK)的最新版本9.0.1中,默认GC被更改为垃圾优先(G1) GC,现在除了以前使用的并行GC和并发标记和扫描(CMS) GC之外,还被广泛采用。由于GC是JVM的重要组成部分,因此对其实现的更改和升级(会影响性能结果)是值得研究的特性。本文使用基准测试来创建重要的内存压力,并使用广泛的数据监控,分析了在几种GC算法中收集到的关于关键性能因素的见解。通过评估基准元素(例如从年轻区域到旧区域的对象分配以及收集时间的持续时间),可以比较GC行为并评估整体内存管理。本文介绍了我们在学术环境下对几个基准案例进行的初步研究以及我们的结论。