Jens Nicolay, Coen De Roover, W. Meuter, V. Jonckers
{"title":"副作用高阶方案程序的自动并行化","authors":"Jens Nicolay, Coen De Roover, W. Meuter, V. Jonckers","doi":"10.1109/SCAM.2011.13","DOIUrl":null,"url":null,"abstract":"The multi-core revolution heralds a challenging era for software maintainers. Manually parallelizing large sequential code bases is often infeasible. In this paper, we present a program transformation that automatically parallelizes real-life Scheme programs. The transformation has to be instantiated with an interprocedural dependence analysis that exposes parallelization opportunities in a sequential program. To this end, we extended a state-of-the art analysis that copes with higher-order procedures and side effects. Our parallelizing transformation exploits all opportunities for parallelization that are exposed by the dependence analysis. Experiments demonstrate that this brute-force approach realizes scalable speedups in certain benchmarks, while others would benefit from a more selective parallelization.","PeriodicalId":286433,"journal":{"name":"2011 IEEE 11th International Working Conference on Source Code Analysis and Manipulation","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Automatic Parallelization of Side-Effecting Higher-Order Scheme Programs\",\"authors\":\"Jens Nicolay, Coen De Roover, W. Meuter, V. Jonckers\",\"doi\":\"10.1109/SCAM.2011.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The multi-core revolution heralds a challenging era for software maintainers. Manually parallelizing large sequential code bases is often infeasible. In this paper, we present a program transformation that automatically parallelizes real-life Scheme programs. The transformation has to be instantiated with an interprocedural dependence analysis that exposes parallelization opportunities in a sequential program. To this end, we extended a state-of-the art analysis that copes with higher-order procedures and side effects. Our parallelizing transformation exploits all opportunities for parallelization that are exposed by the dependence analysis. Experiments demonstrate that this brute-force approach realizes scalable speedups in certain benchmarks, while others would benefit from a more selective parallelization.\",\"PeriodicalId\":286433,\"journal\":{\"name\":\"2011 IEEE 11th International Working Conference on Source Code Analysis and Manipulation\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 11th International Working Conference on Source Code Analysis and Manipulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCAM.2011.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 11th International Working Conference on Source Code Analysis and Manipulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCAM.2011.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Parallelization of Side-Effecting Higher-Order Scheme Programs
The multi-core revolution heralds a challenging era for software maintainers. Manually parallelizing large sequential code bases is often infeasible. In this paper, we present a program transformation that automatically parallelizes real-life Scheme programs. The transformation has to be instantiated with an interprocedural dependence analysis that exposes parallelization opportunities in a sequential program. To this end, we extended a state-of-the art analysis that copes with higher-order procedures and side effects. Our parallelizing transformation exploits all opportunities for parallelization that are exposed by the dependence analysis. Experiments demonstrate that this brute-force approach realizes scalable speedups in certain benchmarks, while others would benefit from a more selective parallelization.