Andreas Wilhelm, Faris Cakaric, M. Gerndt, T. Schüle
{"title":"Tool-Based Interactive Software Parallelization: A Case Study","authors":"Andreas Wilhelm, Faris Cakaric, M. Gerndt, T. Schüle","doi":"10.1145/3183519.3183555","DOIUrl":null,"url":null,"abstract":"Continuous advances in multicore processor technology have placed immense pressure on the software industry. Developers are forced to parallelize their applications to make them scalable. However, applications are often very large and inherently complex; here, automatic parallelization methods are inappropriate. A dependable software redesign requires profound comprehension of the underlying software architecture and its dynamic behavior. To address this problem, we propose Parceive, a tool that supports identification of parallelization scenarios at various levels of abstraction. Parceive collects behavior information at runtime and combines it with reconstructed software architecture information to generate useful visualizations for parallelization. In this paper, we motivate our approach and explain the main components of Parceive. A case study demonstrates the usefulness of the tool.","PeriodicalId":445513,"journal":{"name":"2018 IEEE/ACM 40th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/ACM 40th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3183519.3183555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Continuous advances in multicore processor technology have placed immense pressure on the software industry. Developers are forced to parallelize their applications to make them scalable. However, applications are often very large and inherently complex; here, automatic parallelization methods are inappropriate. A dependable software redesign requires profound comprehension of the underlying software architecture and its dynamic behavior. To address this problem, we propose Parceive, a tool that supports identification of parallelization scenarios at various levels of abstraction. Parceive collects behavior information at runtime and combines it with reconstructed software architecture information to generate useful visualizations for parallelization. In this paper, we motivate our approach and explain the main components of Parceive. A case study demonstrates the usefulness of the tool.