{"title":"Assessing Safe Task Parallelism in SPEC 2006 INT","authors":"Tongxin Bai, C. Ding, Pengcheng Li","doi":"10.1109/CCGrid.2015.159","DOIUrl":null,"url":null,"abstract":"To migrate complex sequential code to multicore, profiling is often used on sequential executions to find opportunities for parallelization. In non-scientific code, the potential parallelism often resides in while-loops rather than for-loops. The do-all model used in the past by many studies cannot detect this type of parallelism. A new, task-based model has been used by a number of recent studies and shown safe for general loops and functions. This paper presents a feedback-based compiler that measures the amount of safe task parallelism in a program and ranks the potential candidates. It solves two problems unique for task analysis. The first is the relation between loop parallelism and function parallelism. The second is the effect of the calling context. The new tool is built in the GCC compiler and used to analyze the entire suite of SPEC 2006 integer benchmarks.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"50 1","pages":"402-411"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2015.159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
To migrate complex sequential code to multicore, profiling is often used on sequential executions to find opportunities for parallelization. In non-scientific code, the potential parallelism often resides in while-loops rather than for-loops. The do-all model used in the past by many studies cannot detect this type of parallelism. A new, task-based model has been used by a number of recent studies and shown safe for general loops and functions. This paper presents a feedback-based compiler that measures the amount of safe task parallelism in a program and ranks the potential candidates. It solves two problems unique for task analysis. The first is the relation between loop parallelism and function parallelism. The second is the effect of the calling context. The new tool is built in the GCC compiler and used to analyze the entire suite of SPEC 2006 integer benchmarks.