{"title":"了解CMP性能优化在数据挖掘应用程序上的适用性","authors":"Ivan Jibaja, K. Shaw","doi":"10.1109/IISWC.2009.5306779","DOIUrl":null,"url":null,"abstract":"A major challenge to the creation of chip multiprocessors is designing the on-chip memory and communication resources to efficiently support parallel workloads. A variety of cache organizations, data management techniques, and hardware optimizations that take advantage of specific data characteristics have been developed to improve application performance. The success of these approaches depends on applications exhibiting the presumed data characteristics.","PeriodicalId":387816,"journal":{"name":"2009 IEEE International Symposium on Workload Characterization (IISWC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Understanding the applicability of CMP performance optimizations on data mining applications\",\"authors\":\"Ivan Jibaja, K. Shaw\",\"doi\":\"10.1109/IISWC.2009.5306779\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A major challenge to the creation of chip multiprocessors is designing the on-chip memory and communication resources to efficiently support parallel workloads. A variety of cache organizations, data management techniques, and hardware optimizations that take advantage of specific data characteristics have been developed to improve application performance. The success of these approaches depends on applications exhibiting the presumed data characteristics.\",\"PeriodicalId\":387816,\"journal\":{\"name\":\"2009 IEEE International Symposium on Workload Characterization (IISWC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Symposium on Workload Characterization (IISWC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IISWC.2009.5306779\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Symposium on Workload Characterization (IISWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISWC.2009.5306779","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Understanding the applicability of CMP performance optimizations on data mining applications
A major challenge to the creation of chip multiprocessors is designing the on-chip memory and communication resources to efficiently support parallel workloads. A variety of cache organizations, data management techniques, and hardware optimizations that take advantage of specific data characteristics have been developed to improve application performance. The success of these approaches depends on applications exhibiting the presumed data characteristics.