Rui Hou, Lixin Zhang, Michael C. Huang, Kun Wang, H. Franke, Y. Ge, Xiaotao Chang
{"title":"片上加速器的高效数据流:机遇与挑战","authors":"Rui Hou, Lixin Zhang, Michael C. Huang, Kun Wang, H. Franke, Y. Ge, Xiaotao Chang","doi":"10.1109/HPCA.2011.5749739","DOIUrl":null,"url":null,"abstract":"The transistor density of microprocessors continues to increase as technology scales. Microprocessors designers have taken advantage of the increased transistors by integrating a significant number of cores onto a single die. However, a large number of cores are met with diminishing returns due to software and hardware scalability issues and hence designers have started integrating on-chip special-purpose logic units (i.e., accelerators) that were previously available as PCI-attached units. It is anticipated that more accelerators will be integrated on-chip due to the increasing abundance of transistors and the fact that not all logic can be powered at all times due to power budget limits. Thus, on-chip accelerator architectures deserve more attention from the research community. There is a wide spectrum of research opportunities for design and optimization of accelerators. This paper attempts to bring out some insights by studying the data access streams of on-chip accelerators that hopefully foster some future research in this area. Specifically, this paper uses a few simple case studies to show some of the common characteristics of the data streams introduced by on-chip accelerators, discusses challenges and opportunities in exploiting these characteristics to optimize the power and performance of accelerators, and then analyzes the effectiveness of some simple optimizing extensions proposed.","PeriodicalId":126976,"journal":{"name":"2011 IEEE 17th International Symposium on High Performance Computer Architecture","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Efficient data streaming with on-chip accelerators: Opportunities and challenges\",\"authors\":\"Rui Hou, Lixin Zhang, Michael C. Huang, Kun Wang, H. Franke, Y. Ge, Xiaotao Chang\",\"doi\":\"10.1109/HPCA.2011.5749739\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The transistor density of microprocessors continues to increase as technology scales. Microprocessors designers have taken advantage of the increased transistors by integrating a significant number of cores onto a single die. However, a large number of cores are met with diminishing returns due to software and hardware scalability issues and hence designers have started integrating on-chip special-purpose logic units (i.e., accelerators) that were previously available as PCI-attached units. It is anticipated that more accelerators will be integrated on-chip due to the increasing abundance of transistors and the fact that not all logic can be powered at all times due to power budget limits. Thus, on-chip accelerator architectures deserve more attention from the research community. There is a wide spectrum of research opportunities for design and optimization of accelerators. This paper attempts to bring out some insights by studying the data access streams of on-chip accelerators that hopefully foster some future research in this area. Specifically, this paper uses a few simple case studies to show some of the common characteristics of the data streams introduced by on-chip accelerators, discusses challenges and opportunities in exploiting these characteristics to optimize the power and performance of accelerators, and then analyzes the effectiveness of some simple optimizing extensions proposed.\",\"PeriodicalId\":126976,\"journal\":{\"name\":\"2011 IEEE 17th International Symposium on High Performance Computer Architecture\",\"volume\":\"91 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-02-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 17th International Symposium on High Performance Computer Architecture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCA.2011.5749739\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 17th International Symposium on High Performance Computer Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2011.5749739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient data streaming with on-chip accelerators: Opportunities and challenges
The transistor density of microprocessors continues to increase as technology scales. Microprocessors designers have taken advantage of the increased transistors by integrating a significant number of cores onto a single die. However, a large number of cores are met with diminishing returns due to software and hardware scalability issues and hence designers have started integrating on-chip special-purpose logic units (i.e., accelerators) that were previously available as PCI-attached units. It is anticipated that more accelerators will be integrated on-chip due to the increasing abundance of transistors and the fact that not all logic can be powered at all times due to power budget limits. Thus, on-chip accelerator architectures deserve more attention from the research community. There is a wide spectrum of research opportunities for design and optimization of accelerators. This paper attempts to bring out some insights by studying the data access streams of on-chip accelerators that hopefully foster some future research in this area. Specifically, this paper uses a few simple case studies to show some of the common characteristics of the data streams introduced by on-chip accelerators, discusses challenges and opportunities in exploiting these characteristics to optimize the power and performance of accelerators, and then analyzes the effectiveness of some simple optimizing extensions proposed.