DocumentCode
1358600
Title
Tera-Scale Performance Machine Learning SoC (MLSoC) With Dual Stream Processor Architecture for Multimedia Content Analysis
Author
Chen, Tse-Wei ; Tang, Chi-Sun ; Tsai, Sung-Fang ; Tsai, Chen-Han ; Chien, Shao-Yi ; Chen, Liang-Gee
Author_Institution
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Volume
45
Issue
11
fYear
2010
Firstpage
2321
Lastpage
2329
Abstract
A new machine learning SoC (MLSoC) for multimedia content analysis is implemented with 16-mm2 area in 90-nm CMOS technology. Different from traditional VLSI architectures, it focuses on the coacceleration of computer vision and machine learning algorithms, and two stream processors with massively parallel processing elements are integrated to achieve tera-scale performance. In the dual stream processor (DSP) architecture, the data are transferred between processors and the high-bandwidth dual memory (HBDM) through the local media bus without consuming the AMBA AHB bandwidth. The image stream processor (ISP) of the MLSoC can handle common window-based operations for image processing, and the feature stream processor (FSP) can deal with machine learning algorithms with different dimensions. The power efficiency of the proposed MLSoC is 1.7 TOPS/W, and the area efficiency is 81.3 GOPS/mm 2.
Keywords
computer vision; digital circuits; learning (artificial intelligence); multimedia systems; system-on-chip; CMOS technology; computer vision; dual stream processor architecture; feature stream processor; image stream processor; multimedia content analysis; tera-scale performance machine learning SoC; Bandwidth; Computer architecture; Digital signal processing; Machine learning algorithms; Multimedia communication; Pixel; Streaming media; Digital circuit; hardware architecture; machine learning; multimedia content analysis; system-on-a-Chip (SoC);
fLanguage
English
Journal_Title
Solid-State Circuits, IEEE Journal of
Publisher
ieee
ISSN
0018-9200
Type
jour
DOI
10.1109/JSSC.2010.2067910
Filename
5607247
Link To Document