{"title":"tile - mapreduce:通过平铺优化多核数据并行应用程序的资源使用","authors":"Rong-Xin Chen, Haibo Chen, B. Zang","doi":"10.1145/1854273.1854337","DOIUrl":null,"url":null,"abstract":"The prevalence of chip multiprocessor opens opportunities of running data-parallel applications originally in clusters on a single machine with many cores. MapReduce, a simple and elegant programming model to program large scale clusters, has recently been shown to be a promising alternative to harness the multicore platform.","PeriodicalId":422461,"journal":{"name":"2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"130","resultStr":"{\"title\":\"Tiled-MapReduce: Optimizing resource usages of data-parallel applications on multicore with tiling\",\"authors\":\"Rong-Xin Chen, Haibo Chen, B. Zang\",\"doi\":\"10.1145/1854273.1854337\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The prevalence of chip multiprocessor opens opportunities of running data-parallel applications originally in clusters on a single machine with many cores. MapReduce, a simple and elegant programming model to program large scale clusters, has recently been shown to be a promising alternative to harness the multicore platform.\",\"PeriodicalId\":422461,\"journal\":{\"name\":\"2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"130\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1854273.1854337\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1854273.1854337","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tiled-MapReduce: Optimizing resource usages of data-parallel applications on multicore with tiling
The prevalence of chip multiprocessor opens opportunities of running data-parallel applications originally in clusters on a single machine with many cores. MapReduce, a simple and elegant programming model to program large scale clusters, has recently been shown to be a promising alternative to harness the multicore platform.
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