Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: High-Performance Computing
Guest editors: Achyut Shankar
Article type: Research Article
Authors: Li, Haiqianga | Ling, Zhimeib | Yang, Chaoyib; *
Affiliations: [a] College of Commerce and Economic Management, Huzhou Vocational and Technical College, Huzhou, China | [b] School of Economics and Management, Taishan University, Tai’an, China
Correspondence: [*] Corresponding author: Chaoyi Yang, School of Economics and Management, Taishan University, Tai’an 271000, China. E-mail: ChaoYi_Yang24@outlook.com.
Abstract: With the digital transformation of information technology and industry, the applicability scenarios of edge intelligent terminals are expanding. AI chips have become one of the mainstream core devices of edge terminals. How to select suitable AI chips according to application scenarios through systematic analysis has become an urgent problem to be solved. This paper first provides a comparative analysis of the technical architecture and advantages and disadvantages of AI chips; then proposes a low implementation complexity, multi-code rate fusion LDPC parallel coding structure, and an encoder chip design scheme using this structure for high-speed digital transmission applications. Based on the TSMC 130 nm CMOS standard cell library, the encoder chip can achieve a throughput rate of 1.6 Gbps at 200 MHz clock and consume only 184.3 m W. Compared with the LDPC encoder chip with the same throughput rate designed in the conventional architecture, this solution can reduce the storage space requirement to 18.52% of the conventional architecture. The proposed encoding chip design solution not only maintains high performance but also significantly reduces the demand for storage space, making it a good choice for resource-constrained environments.
Keywords: AI chip, edge intelligence, LDPC encoder, multi-code rate fusion, integrated chip design
DOI: 10.3233/IDT-240112
Journal: Intelligent Decision Technologies, vol. 18, no. 4, pp. 3259-3276, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl