Tomofumi Yuki, P. Feautrier, S. Rajopadhye, V. Saraswat
{"title":"Array dataflow analysis for polyhedral X10 programs","authors":"Tomofumi Yuki, P. Feautrier, S. Rajopadhye, V. Saraswat","doi":"10.1145/2442516.2442520","DOIUrl":null,"url":null,"abstract":"This paper addresses the static analysis of an important class of X10 programs, namely those with finish/async parallelism, and affine loops and array reference structure as in the polyhedral model. For such programs our analysis can certify whenever a program is deterministic or flags races.\n Our key contributions are (i) adaptation of array dataflow analysis from the polyhedral model to programs with finish/async parallelism, and (ii) use of the array dataflow analysis result to certify determinacy. We distinguish our work from previous approaches by combining the precise statement instance-wise and array element-wise analysis capability of the polyhedral model with finish/async programs that are more expressive than doall parallelism commonly considered in the polyhedral literature. We show that our approach is exact (no false negative/positives) and more precise than previous approaches, but is limited to programs that fit the polyhedral model.","PeriodicalId":286119,"journal":{"name":"ACM SIGPLAN Symposium on Principles & Practice of Parallel Programming","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGPLAN Symposium on Principles & Practice of Parallel Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2442516.2442520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
This paper addresses the static analysis of an important class of X10 programs, namely those with finish/async parallelism, and affine loops and array reference structure as in the polyhedral model. For such programs our analysis can certify whenever a program is deterministic or flags races.
Our key contributions are (i) adaptation of array dataflow analysis from the polyhedral model to programs with finish/async parallelism, and (ii) use of the array dataflow analysis result to certify determinacy. We distinguish our work from previous approaches by combining the precise statement instance-wise and array element-wise analysis capability of the polyhedral model with finish/async programs that are more expressive than doall parallelism commonly considered in the polyhedral literature. We show that our approach is exact (no false negative/positives) and more precise than previous approaches, but is limited to programs that fit the polyhedral model.