Fine-Grained CPU Power Management Based on Digital Frequency Divider

doi:10.3390/electronics12020407

	Fine-Grained CPU Power Management Based on Digital Frequency Divider
	Jia, Fan 1,2; Zhang, Longbing 1
	2023
发表期刊	ELECTRONICS
卷号	12 期号:2 页码:18
摘要	Dynamic voltage and frequency scaling (DVFS) is a widely used method to improve the energy efficiency of the CPU. Reducing the voltage and frequency during memory-intensive workloads can minimize power consumption without affecting performance, thereby improving overall energy efficiency. A finer-grained DVFS strategy leads to better energy efficiency. However, due to the limitation of voltage regulators, the implementation granularity of the current DVFS strategies is 100 mu s or more. This paper proposes that managing the CPU's power through a more fine-grained load-aware approach can improve CPU energy efficiency, even with limitations of the voltage regulators. This paper adds a more fine-grained dynamic frequency divider to the DVFS system. This mechanism can improve the processor's energy efficiency in scenarios where DVFS does not take effect. This paper also proposes a DVFS management strategy based on finer-grained sampling. In order to improve the accuracy of performance estimation, we enhanced the state-of-the-art CRIT method to complete accurate memory time estimation in a shorter interval. The power management strategy was verified on the ChampSim and McPAT simulating platforms. In the SPEC CPU 2017 benchmark, this work saves an average of 16.36% energy consumption and improves energy efficiency by 13.57%. Compared with the state-of-the-art CRIT of 9.77% and 6.79%, this work improved energy consumption and efficiency by 6.20% and 6.35%, respectively. This method brings a 2.04% performance reduction, only a 0.16% drop in performance compared to CRIT.
关键词	power management workloads sensing critical path of memory access DVFS digital frequency divider
DOI	10.3390/electronics12020407
收录类别	SCI
语种	英语
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDC05020100]
WOS研究方向	Computer Science ; Engineering ; Physics
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Physics, Applied
WOS记录号	WOS:000917317400001
出版者	MDPI
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/20018
专题	中国科学院计算技术研究所期刊论文
通讯作者	Jia, Fan
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Microprocessor Technol Res Ctr, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
推荐引用方式 GB/T 7714	Jia, Fan,Zhang, Longbing. Fine-Grained CPU Power Management Based on Digital Frequency Divider[J]. ELECTRONICS,2023,12(2):18.
APA	Jia, Fan,&Zhang, Longbing.(2023).Fine-Grained CPU Power Management Based on Digital Frequency Divider.ELECTRONICS,12(2),18.
MLA	Jia, Fan,et al."Fine-Grained CPU Power Management Based on Digital Frequency Divider".ELECTRONICS 12.2(2023):18.