Mary W. Hall, Jennifer M. Anderson, Saman P. Amarasinghe, Brian R. Murphy, Shih-Wei Liao, Edouard Bugnion, M. Lam
{"title":"最大化多处理器性能与SUIF编译器","authors":"Mary W. Hall, Jennifer M. Anderson, Saman P. Amarasinghe, Brian R. Murphy, Shih-Wei Liao, Edouard Bugnion, M. Lam","doi":"10.1109/2.546613","DOIUrl":null,"url":null,"abstract":"This article describes automatic parallelization techniques in the SUIF (Stanford University Intermediate Format) compiler that result in good multiprocessor performance for array-based numerical programs. Parallelizing compilers for multiprocessors face many hurdles. However, SUIF's robust analysis and memory optimization techniques enabled speedups on three fourths of the NAS and SPECfp95 benchmark programs.","PeriodicalId":253466,"journal":{"name":"Digit. Tech. J.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"638","resultStr":"{\"title\":\"Maximizing Multiprocessor Performance with the SUIF Compiler\",\"authors\":\"Mary W. Hall, Jennifer M. Anderson, Saman P. Amarasinghe, Brian R. Murphy, Shih-Wei Liao, Edouard Bugnion, M. Lam\",\"doi\":\"10.1109/2.546613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article describes automatic parallelization techniques in the SUIF (Stanford University Intermediate Format) compiler that result in good multiprocessor performance for array-based numerical programs. Parallelizing compilers for multiprocessors face many hurdles. However, SUIF's robust analysis and memory optimization techniques enabled speedups on three fourths of the NAS and SPECfp95 benchmark programs.\",\"PeriodicalId\":253466,\"journal\":{\"name\":\"Digit. Tech. J.\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"638\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digit. Tech. J.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/2.546613\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digit. Tech. J.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/2.546613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 638
摘要
本文描述了SUIF (Stanford University Intermediate Format)编译器中的自动并行化技术,它为基于数组的数值程序带来了良好的多处理器性能。多处理器的并行编译器面临许多障碍。然而,SUIF强大的分析和内存优化技术使四分之三的NAS和SPECfp95基准程序提速。
Maximizing Multiprocessor Performance with the SUIF Compiler
This article describes automatic parallelization techniques in the SUIF (Stanford University Intermediate Format) compiler that result in good multiprocessor performance for array-based numerical programs. Parallelizing compilers for multiprocessors face many hurdles. However, SUIF's robust analysis and memory optimization techniques enabled speedups on three fourths of the NAS and SPECfp95 benchmark programs.