生成CPU压力测试的自动框架

Zacharias Hadjilambrou, Shidhartha Das, P. Whatmough, David M. Bull, Yiannakis Sazeides
{"title":"生成CPU压力测试的自动框架","authors":"Zacharias Hadjilambrou, Shidhartha Das, P. Whatmough, David M. Bull, Yiannakis Sazeides","doi":"10.1109/ISPASS.2019.00009","DOIUrl":null,"url":null,"abstract":"This work presents GeST (Generator for Stress-Tests): a framework for automatically generating CPU stress-tests. The framework is based on genetic algorithm search and can be used to maximize different target CPU metrics such as power, temperature, instructions executed per cycle and dl/dt voltage noise. We demonstrate the generality and effectiveness of the framework by generating various workloads that stress the CPU power, thermal and voltage margins more than both conventional benchmarks and manually written stress-tests. The key framework strengths are its extensibility and flexibility. The user can specify custom measurement and fitness functions as well as the CPU instructions that will be used in the genetic algorithm search. The paper demonstrates the framework prowess by using it with simple and complex fitness functions to generate stress-tests: a) for various platform types ranging from low-power mobile ARM CPUs to high-power x86 CPUs and b) with different measurement instruments such as oscilloscopes and software accessible performance counters and sensors.","PeriodicalId":137786,"journal":{"name":"2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"GeST: An Automatic Framework For Generating CPU Stress-Tests\",\"authors\":\"Zacharias Hadjilambrou, Shidhartha Das, P. Whatmough, David M. Bull, Yiannakis Sazeides\",\"doi\":\"10.1109/ISPASS.2019.00009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work presents GeST (Generator for Stress-Tests): a framework for automatically generating CPU stress-tests. The framework is based on genetic algorithm search and can be used to maximize different target CPU metrics such as power, temperature, instructions executed per cycle and dl/dt voltage noise. We demonstrate the generality and effectiveness of the framework by generating various workloads that stress the CPU power, thermal and voltage margins more than both conventional benchmarks and manually written stress-tests. The key framework strengths are its extensibility and flexibility. The user can specify custom measurement and fitness functions as well as the CPU instructions that will be used in the genetic algorithm search. The paper demonstrates the framework prowess by using it with simple and complex fitness functions to generate stress-tests: a) for various platform types ranging from low-power mobile ARM CPUs to high-power x86 CPUs and b) with different measurement instruments such as oscilloscopes and software accessible performance counters and sensors.\",\"PeriodicalId\":137786,\"journal\":{\"name\":\"2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)\",\"volume\":\"117 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPASS.2019.00009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPASS.2019.00009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

这项工作展示了GeST(压力测试生成器):一个用于自动生成CPU压力测试的框架。该框架基于遗传算法搜索,可用于最大化不同的目标CPU指标,如功率、温度、每周期执行的指令和dl/dt电压噪声。我们通过生成各种工作负载来展示框架的通用性和有效性,这些工作负载比传统基准测试和手动编写的压力测试对CPU功率、热和电压裕度的压力更大。框架的主要优势在于它的可扩展性和灵活性。用户可以指定自定义的测量和健身功能,以及将用于遗传算法搜索的CPU指令。本文通过将框架与简单和复杂的适应度函数一起使用来演示该框架的强大功能,以生成压力测试:a)用于各种平台类型,从低功耗移动ARM cpu到高功耗x86 cpu, b)使用不同的测量仪器,如示波器和软件可访问的性能计数器和传感器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GeST: An Automatic Framework For Generating CPU Stress-Tests
This work presents GeST (Generator for Stress-Tests): a framework for automatically generating CPU stress-tests. The framework is based on genetic algorithm search and can be used to maximize different target CPU metrics such as power, temperature, instructions executed per cycle and dl/dt voltage noise. We demonstrate the generality and effectiveness of the framework by generating various workloads that stress the CPU power, thermal and voltage margins more than both conventional benchmarks and manually written stress-tests. The key framework strengths are its extensibility and flexibility. The user can specify custom measurement and fitness functions as well as the CPU instructions that will be used in the genetic algorithm search. The paper demonstrates the framework prowess by using it with simple and complex fitness functions to generate stress-tests: a) for various platform types ranging from low-power mobile ARM CPUs to high-power x86 CPUs and b) with different measurement instruments such as oscilloscopes and software accessible performance counters and sensors.
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
自引率
0.00%
发文量
0
×
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:604180095
Book学术官方微信