{"title":"CDTT: Compiler-generated data-triggered threads","authors":"Hung-Wei Tseng, D. Tullsen","doi":"10.1109/HPCA.2014.6835973","DOIUrl":null,"url":null,"abstract":"This paper presents CDTT, a compiler framework that takes C/C++ code and automatically generates a binary that eliminates dynamically redundant code without programmer intervention. It does so by exploiting underlying hardware or software support for the data-triggered threads (DTT) programming and execution model. With the help of idempotence analysis and inter-procedural name dependence analysis, CDTT identifies potential code regions and composes support thread functions that execute as soon as live-in data changes. CDTT can also use profile data to target the elimination of redundant computation. The compiled binary running on top of a software runtime system can achieve nearly the same level of performance as careful hand-coded modifications in most benchmarks. CDTT improves the performance of serial C SPEC benchmarks by as much as 57% (average 11%) on a Nehalem processor.","PeriodicalId":164587,"journal":{"name":"2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2014.6835973","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper presents CDTT, a compiler framework that takes C/C++ code and automatically generates a binary that eliminates dynamically redundant code without programmer intervention. It does so by exploiting underlying hardware or software support for the data-triggered threads (DTT) programming and execution model. With the help of idempotence analysis and inter-procedural name dependence analysis, CDTT identifies potential code regions and composes support thread functions that execute as soon as live-in data changes. CDTT can also use profile data to target the elimination of redundant computation. The compiled binary running on top of a software runtime system can achieve nearly the same level of performance as careful hand-coded modifications in most benchmarks. CDTT improves the performance of serial C SPEC benchmarks by as much as 57% (average 11%) on a Nehalem processor.