{"title":"评估数据中心工作负载的集成图形处理器","authors":"Sangman Kim, Indrajit Roy, V. Talwar","doi":"10.1145/2525526.2525847","DOIUrl":null,"url":null,"abstract":"More than 90% of consumer computers use integrated graphics processors. In these processors, the CPU and the GPU share the same physical memory. Due to high density, good power efficiency, and low cost, integrated graphics processors are promising candidates for next-generation micro-servers and, hence, data-center workloads.\n While discrete graphics processors have been extensively studied, there is very little work on characterizing integrated GPUs. This paper is a step towards understanding the power and performance of integrated GPUs. Our results reveal many architectural caveats that programmers need to be aware of to exploit integrated GPUs: memory contention between the CPU and GPU, workload dependent energy efficiency, and data transfer tradeoffs.","PeriodicalId":112226,"journal":{"name":"Power-Aware Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Evaluating integrated graphics processors for data center workloads\",\"authors\":\"Sangman Kim, Indrajit Roy, V. Talwar\",\"doi\":\"10.1145/2525526.2525847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"More than 90% of consumer computers use integrated graphics processors. In these processors, the CPU and the GPU share the same physical memory. Due to high density, good power efficiency, and low cost, integrated graphics processors are promising candidates for next-generation micro-servers and, hence, data-center workloads.\\n While discrete graphics processors have been extensively studied, there is very little work on characterizing integrated GPUs. This paper is a step towards understanding the power and performance of integrated GPUs. Our results reveal many architectural caveats that programmers need to be aware of to exploit integrated GPUs: memory contention between the CPU and GPU, workload dependent energy efficiency, and data transfer tradeoffs.\",\"PeriodicalId\":112226,\"journal\":{\"name\":\"Power-Aware Computer Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Power-Aware Computer Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2525526.2525847\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Power-Aware Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2525526.2525847","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating integrated graphics processors for data center workloads
More than 90% of consumer computers use integrated graphics processors. In these processors, the CPU and the GPU share the same physical memory. Due to high density, good power efficiency, and low cost, integrated graphics processors are promising candidates for next-generation micro-servers and, hence, data-center workloads.
While discrete graphics processors have been extensively studied, there is very little work on characterizing integrated GPUs. This paper is a step towards understanding the power and performance of integrated GPUs. Our results reveal many architectural caveats that programmers need to be aware of to exploit integrated GPUs: memory contention between the CPU and GPU, workload dependent energy efficiency, and data transfer tradeoffs.