LMM: A Fixed-Point Linear Mapping Based Approximate Multiplier for IoT

doi:10.1007/s11390-023-2572-8

	LMM: A Fixed-Point Linear Mapping Based Approximate Multiplier for IoT
	Qian, Wei-Kang 1; Chen, Ke 2; Liu, Wei-Qiang 2; Li, Hua-Wei 3
	2023-04-01
发表期刊	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
ISSN	1000-9000
卷号	38 期号:2 页码:298-308
摘要	The development of IoT (Internet of Things) calls for circuit designs with energy and area efficiency for edge devices. Approximate computing which trades unnecessary computation precision for hardware cost savings is a promising direction for error-tolerant applications. Multipliers, as frequently invoked basic modules which consume non-trivial hardware costs, have been introduced approximation to achieve distinct energy and area savings for data-intensive applications. In this paper, we propose a fixed-point approximate multiplier that employs a linear mapping technique, which enables the configurability of approximation levels and the unbiasedness of computation errors. We then introduce a dynamic truncation method into the proposed multiplier design to cover a wider and more fine-grained configuration range of approximation for more flexible hardware cost savings. In addition, a novel normalization module is proposed for the required shifting operations, which balances the occupied area and the critical path delay compared with normal shifters. The introduced errors of our proposed design are analyzed and expressed by formulas which are validated by experimental results. Experimental evaluations show that compared with accurate multipliers, our proposed approximate multiplier design provides maximum area and power savings up to 49.70% and 66.39% respectively with acceptable computation errors.
关键词	approximate computing fixed-point linear mapping multiplier Internet of Things (IoT)
DOI	10.1007/s11390-023-2572-8
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS记录号	WOS:001017832400007
出版者	SPRINGER SINGAPORE PTE LTD
引用统计	被引频次：1[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/2XEOYT63/21306
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Qian, Wei-Kang
作者单位	1.Shanghai Jiao Tong Univ, Univ Michigan Shanghai Jiao Tong Univ Joint Inst, Shanghai, Peoples R China 2.Nanjing Univ Aeronaut & Astronaut, Coll Elect & Informat Engn, Nanjing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Qian, Wei-Kang,Chen, Ke,Liu, Wei-Qiang,et al. LMM: A Fixed-Point Linear Mapping Based Approximate Multiplier for IoT[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2023,38(2):298-308.
APA	Qian, Wei-Kang,Chen, Ke,Liu, Wei-Qiang,&Li, Hua-Wei.(2023).LMM: A Fixed-Point Linear Mapping Based Approximate Multiplier for IoT.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,38(2),298-308.
MLA	Qian, Wei-Kang,et al."LMM: A Fixed-Point Linear Mapping Based Approximate Multiplier for IoT".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 38.2(2023):298-308.