Evaluation and choice of various branch predictors for low-power embedded processor
文献类型:期刊论文
作者 | Fan, DR; Yang, HB; Gao, GR; Zhao, RC |
刊名 | JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
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出版日期 | 2003-11-01 |
卷号 | 18期号:6页码:833-838 |
关键词 | branch predictor embedded processor |
ISSN号 | 1000-9000 |
英文摘要 | Power is an important design constraint in embedded computing systems. To meet the power constraint, microarchitecture and hardware designed to achieve high performance need to be revisited, from both performance and power angles. This paper studies one of them: branch predictor. As well known, branch prediction is critical to exploit instruction level parallelism effectively, but may incur additional power consumption due to the hardware resource dedicated for branch prediction and the extra power consumed on mispredicted branches. This paper explores the design space of branch prediction mechanisms and tries to find the most beneficial one to realize low-power embedded processor. The sample processor studied is Godson-like processor, which is a dual-issue, out-of-order processor with deep pipeline, supporting MIPS instruction set. |
WOS研究方向 | Computer Science |
语种 | 英语 |
WOS记录号 | WOS:000187161600018 |
出版者 | SCIENCE PRESS |
源URL | [http://119.78.100.204/handle/2XEOYT63/13637] ![]() |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Fan, DR |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China 2.Univ Delaware, Dept Elect & Comp Engn, Newark, DE 19716 USA |
推荐引用方式 GB/T 7714 | Fan, DR,Yang, HB,Gao, GR,et al. Evaluation and choice of various branch predictors for low-power embedded processor[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2003,18(6):833-838. |
APA | Fan, DR,Yang, HB,Gao, GR,&Zhao, RC.(2003).Evaluation and choice of various branch predictors for low-power embedded processor.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,18(6),833-838. |
MLA | Fan, DR,et al."Evaluation and choice of various branch predictors for low-power embedded processor".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 18.6(2003):833-838. |
入库方式: OAI收割
来源:计算技术研究所
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