Processor Design Space Exploration via Statistical Sampling and Semi-Supervised Ensemble Learning

doi:10.1109/ACCESS.2018.2831079

	Processor Design Space Exploration via Statistical Sampling and Semi-Supervised Ensemble Learning
	Li, Dandan 1; Yao, Shuzhen 1; Wang, Ying 2
	2018
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	6 页码:25495-25505
摘要	The design space exploration (DSE) has become a major challenge in microprocessors design due to the increasing complexity of microprocessor architecture and the extremely time-consuming software simulation technology. To more effectively and efficiently perform DSE, recently machine learning techniques are widely explored to build predictive models with a small set of simulations. However, most previous models are supervised models and the training samples are randomly selected. Thus they still suffered from high simulation cost or low prediction accuracy. In order to minimize the simulation overhead for DSE, this paper proposes an efficient DSE method which combines Latin hypercube sampling and semi-supervised ensemble learning technique. Latin hypercube sampling is first employed to select a small set of representative design points for simulation. Then a semi-supervised learning based AdaBoost model (SemiBoost) is proposed to predict the responses of the configurations that have not been simulated. We conduct extensive evaluations on the benchmarks of SPEC CPU2006 suite, and the experimental results demonstrate that the proposed SemiBoost model is superior to existing state-of-the-art models in terms of both efficiency and effectiveness.
关键词	Design space exploration Latin hypercube sampling adaboost microprocessor design
DOI	10.1109/ACCESS.2018.2831079
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61504153] ; National Natural Science Foundation of China[61432017]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000433472100001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5226
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Dandan
作者单位	1.Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Dandan,Yao, Shuzhen,Wang, Ying. Processor Design Space Exploration via Statistical Sampling and Semi-Supervised Ensemble Learning[J]. IEEE ACCESS,2018,6:25495-25505.
APA	Li, Dandan,Yao, Shuzhen,&Wang, Ying.(2018).Processor Design Space Exploration via Statistical Sampling and Semi-Supervised Ensemble Learning.IEEE ACCESS,6,25495-25505.
MLA	Li, Dandan,et al."Processor Design Space Exploration via Statistical Sampling and Semi-Supervised Ensemble Learning".IEEE ACCESS 6(2018):25495-25505.