Faiz Khan, Vincent Foley-Bourgon, Sujay Kathrotia, Erick Lavoie, L. Hendren
{"title":"Using JavaScript and WebCL for numerical computations: a comparative study of native and web technologies","authors":"Faiz Khan, Vincent Foley-Bourgon, Sujay Kathrotia, Erick Lavoie, L. Hendren","doi":"10.1145/2661088.2661090","DOIUrl":null,"url":null,"abstract":"From its modest beginnings as a tool to validate forms, JavaScript is now an industrial-strength language used to power online applications such as spreadsheets, IDEs, image editors and even 3D games. Since all modern web browsers support JavaScript, it provides a medium that is both easy to distribute for developers and easy to access for users. This paper provides empirical data to answer the question: Is JavaScript fast enough for numerical computations? By measuring and comparing the runtime performance of benchmarks representative of a wide variety of scientific applications, we show that sequential JavaScript is within a factor of 2 of native code. Parallel code using WebCL shows speed improvements of up to 2.28 over JavaScript for the majority of the benchmarks.","PeriodicalId":244838,"journal":{"name":"Proceedings of the 10th ACM Symposium on Dynamic languages","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 10th ACM Symposium on Dynamic languages","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2661088.2661090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35
Abstract
From its modest beginnings as a tool to validate forms, JavaScript is now an industrial-strength language used to power online applications such as spreadsheets, IDEs, image editors and even 3D games. Since all modern web browsers support JavaScript, it provides a medium that is both easy to distribute for developers and easy to access for users. This paper provides empirical data to answer the question: Is JavaScript fast enough for numerical computations? By measuring and comparing the runtime performance of benchmarks representative of a wide variety of scientific applications, we show that sequential JavaScript is within a factor of 2 of native code. Parallel code using WebCL shows speed improvements of up to 2.28 over JavaScript for the majority of the benchmarks.