{"title":"多核时代的计算机科学教育集群","authors":"Joel C. Adams, Kathy Hoobeboom, Jonathan Walz","doi":"10.1145/1953163.1953177","DOIUrl":null,"url":null,"abstract":"Traditional Beowulf clusters have been homogeneous platforms for distributed-memory MIMD parallelism. However, the shift to multicore architectures has made shared-memory MIMD parallelism increasingly important, and inexpensive manycore GPGPUs have revived SIMD parallelism. This paper presents a case study in designing and building a heterogeneous cluster as a learning platform for tera-scale distributed- and shared-memory MIMD parallelism, and GPGPU parallelism.","PeriodicalId":137934,"journal":{"name":"Proceedings of the 42nd ACM technical symposium on Computer science education","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A cluster for CS education in the manycore era\",\"authors\":\"Joel C. Adams, Kathy Hoobeboom, Jonathan Walz\",\"doi\":\"10.1145/1953163.1953177\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional Beowulf clusters have been homogeneous platforms for distributed-memory MIMD parallelism. However, the shift to multicore architectures has made shared-memory MIMD parallelism increasingly important, and inexpensive manycore GPGPUs have revived SIMD parallelism. This paper presents a case study in designing and building a heterogeneous cluster as a learning platform for tera-scale distributed- and shared-memory MIMD parallelism, and GPGPU parallelism.\",\"PeriodicalId\":137934,\"journal\":{\"name\":\"Proceedings of the 42nd ACM technical symposium on Computer science education\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 42nd ACM technical symposium on Computer science education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1953163.1953177\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 42nd ACM technical symposium on Computer science education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1953163.1953177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Traditional Beowulf clusters have been homogeneous platforms for distributed-memory MIMD parallelism. However, the shift to multicore architectures has made shared-memory MIMD parallelism increasingly important, and inexpensive manycore GPGPUs have revived SIMD parallelism. This paper presents a case study in designing and building a heterogeneous cluster as a learning platform for tera-scale distributed- and shared-memory MIMD parallelism, and GPGPU parallelism.
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