OCCAM-v2:结合静态和动态分析实现高效、高效的全程序专业化

Q3 Computer Science
Queue Pub Date : 2022-10-31 DOI:10.1145/3570922
J. Navas, Ashish Gehani
{"title":"OCCAM-v2:结合静态和动态分析实现高效、高效的全程序专业化","authors":"J. Navas, Ashish Gehani","doi":"10.1145/3570922","DOIUrl":null,"url":null,"abstract":"OCCAM-v2 leverages scalable pointer analysis, value analysis, and dynamic analysis to create an effective and efficient tool for specializing LLVM bitcode. The extent of the code-size reduction achieved depends on the specific deployment configuration. Each application that is to be specialized is accompanied by a manifest that specifies concrete arguments that are known a priori, as well as a count of residual arguments that will be provided at runtime. The best case for partial evaluation occurs when the arguments are completely concretely specified. OCCAM-v2 uses a pointer analysis to devirtualize calls, allowing it to eliminate the entire body of functions that are not reachable by any direct calls. The hybrid analysis feature can handle cases that are challenging for static analysis, such as input loops, string processing, and external data (in files, for example). On the suite of evaluated programs, OCCAM-v2 was able to reduce the instruction count by 40.6 percent on average, taking a median of 2.4 seconds.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"58 - 85"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"OCCAM-v2: Combining Static and Dynamic Analysis for Effective and Efficient Whole-program Specialization\",\"authors\":\"J. Navas, Ashish Gehani\",\"doi\":\"10.1145/3570922\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"OCCAM-v2 leverages scalable pointer analysis, value analysis, and dynamic analysis to create an effective and efficient tool for specializing LLVM bitcode. The extent of the code-size reduction achieved depends on the specific deployment configuration. Each application that is to be specialized is accompanied by a manifest that specifies concrete arguments that are known a priori, as well as a count of residual arguments that will be provided at runtime. The best case for partial evaluation occurs when the arguments are completely concretely specified. OCCAM-v2 uses a pointer analysis to devirtualize calls, allowing it to eliminate the entire body of functions that are not reachable by any direct calls. The hybrid analysis feature can handle cases that are challenging for static analysis, such as input loops, string processing, and external data (in files, for example). On the suite of evaluated programs, OCCAM-v2 was able to reduce the instruction count by 40.6 percent on average, taking a median of 2.4 seconds.\",\"PeriodicalId\":39042,\"journal\":{\"name\":\"Queue\",\"volume\":\"20 1\",\"pages\":\"58 - 85\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Queue\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3570922\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Queue","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3570922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 1

摘要

OCCAM-v2利用可扩展的指针分析、值分析和动态分析来创建一个有效和高效的LLVM位码专门化工具。代码大小减少的程度取决于具体的部署配置。每个要专门化的应用程序都伴随着一个清单,其中指定了先验已知的具体参数,以及将在运行时提供的剩余参数的计数。部分求值的最佳情况发生在参数完全具体指定时。OCCAM-v2使用指针分析来实现非虚拟化调用,从而消除任何直接调用都无法访问的整个函数体。混合分析特性可以处理对静态分析具有挑战性的情况,例如输入循环、字符串处理和外部数据(例如文件中的数据)。在评估的程序套件中,OCCAM-v2能够平均减少40.6%的指令计数,中位数为2.4秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OCCAM-v2: Combining Static and Dynamic Analysis for Effective and Efficient Whole-program Specialization
OCCAM-v2 leverages scalable pointer analysis, value analysis, and dynamic analysis to create an effective and efficient tool for specializing LLVM bitcode. The extent of the code-size reduction achieved depends on the specific deployment configuration. Each application that is to be specialized is accompanied by a manifest that specifies concrete arguments that are known a priori, as well as a count of residual arguments that will be provided at runtime. The best case for partial evaluation occurs when the arguments are completely concretely specified. OCCAM-v2 uses a pointer analysis to devirtualize calls, allowing it to eliminate the entire body of functions that are not reachable by any direct calls. The hybrid analysis feature can handle cases that are challenging for static analysis, such as input loops, string processing, and external data (in files, for example). On the suite of evaluated programs, OCCAM-v2 was able to reduce the instruction count by 40.6 percent on average, taking a median of 2.4 seconds.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Queue
Queue Computer Science-Computer Science (all)
CiteScore
1.80
自引率
0.00%
发文量
23
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信