利用指令级资源并行性实现透明、集成的控制流监控

M. Schuette, John Paul Shen
{"title":"利用指令级资源并行性实现透明、集成的控制流监控","authors":"M. Schuette, John Paul Shen","doi":"10.1109/FTCS.1991.146680","DOIUrl":null,"url":null,"abstract":"Available resource-driven control-flow monitoring (ARC), a method for detecting transient errors by using idle resources in processor architectures that use increased degrees of instruction-level parallelism to achieve performance goals, is presented. The focus is on concurrent detection of control-flow errors (CFEs) in VLIW processors. Previous work is reviewed, and ARC monitoring is described as a monitoring computation (MC) that executes concurrently with and continuously monitors the execution of the application computation (AC). The algorithm that integrates the MC into the AC is presented. An analytical derivation of ARC's error coverage is given, and results of applying ARC to four benchmark programs on an actual VLIW processor are reported. Results show that for all the benchmarks, all of the additional operations required by ARC can make use of idle resources, achieving a detection coverage of >99% in all cases. The performance overhead of ARC is found to be negligible, even for programs with relatively few idle resources available.<<ETX>>","PeriodicalId":300397,"journal":{"name":"[1991] Digest of Papers. Fault-Tolerant Computing: The Twenty-First International Symposium","volume":"92 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Exploiting instruction-level resource parallelism for transparent, integrated control-flow monitoring\",\"authors\":\"M. Schuette, John Paul Shen\",\"doi\":\"10.1109/FTCS.1991.146680\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Available resource-driven control-flow monitoring (ARC), a method for detecting transient errors by using idle resources in processor architectures that use increased degrees of instruction-level parallelism to achieve performance goals, is presented. The focus is on concurrent detection of control-flow errors (CFEs) in VLIW processors. Previous work is reviewed, and ARC monitoring is described as a monitoring computation (MC) that executes concurrently with and continuously monitors the execution of the application computation (AC). The algorithm that integrates the MC into the AC is presented. An analytical derivation of ARC's error coverage is given, and results of applying ARC to four benchmark programs on an actual VLIW processor are reported. Results show that for all the benchmarks, all of the additional operations required by ARC can make use of idle resources, achieving a detection coverage of >99% in all cases. The performance overhead of ARC is found to be negligible, even for programs with relatively few idle resources available.<<ETX>>\",\"PeriodicalId\":300397,\"journal\":{\"name\":\"[1991] Digest of Papers. Fault-Tolerant Computing: The Twenty-First International Symposium\",\"volume\":\"92 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991] Digest of Papers. Fault-Tolerant Computing: The Twenty-First International Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FTCS.1991.146680\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Digest of Papers. Fault-Tolerant Computing: The Twenty-First International Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FTCS.1991.146680","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23

摘要

摘要提出了一种利用空闲资源检测暂态错误的方法——可用资源驱动的控制流监控(ARC),该方法通过提高指令级并行度来实现性能目标。重点是VLIW处理器中控制流错误(cfe)的并发检测。回顾了以往的工作,并将ARC监控描述为与应用程序计算(AC)并行执行并持续监控其执行的监控计算(MC)。提出了将MC集成到AC中的算法。给出了ARC的错误覆盖率的解析推导,并报道了在实际VLIW处理器上将ARC应用于四个基准程序的结果。结果表明,对于所有基准测试,ARC所需的所有附加操作都可以利用空闲资源,在所有情况下实现>99%的检测覆盖率。ARC的性能开销被发现可以忽略不计,即使对于可用的空闲资源相对较少的程序也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploiting instruction-level resource parallelism for transparent, integrated control-flow monitoring
Available resource-driven control-flow monitoring (ARC), a method for detecting transient errors by using idle resources in processor architectures that use increased degrees of instruction-level parallelism to achieve performance goals, is presented. The focus is on concurrent detection of control-flow errors (CFEs) in VLIW processors. Previous work is reviewed, and ARC monitoring is described as a monitoring computation (MC) that executes concurrently with and continuously monitors the execution of the application computation (AC). The algorithm that integrates the MC into the AC is presented. An analytical derivation of ARC's error coverage is given, and results of applying ARC to four benchmark programs on an actual VLIW processor are reported. Results show that for all the benchmarks, all of the additional operations required by ARC can make use of idle resources, achieving a detection coverage of >99% in all cases. The performance overhead of ARC is found to be negligible, even for programs with relatively few idle resources available.<>
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