DocumentCode
1962777
Title
Word-parallel coprocessor architecture for digital nearest Euclidean distance search
Author
Akazawa, Toshinobu ; Sasaki, Seishi ; Mattausch, Hans Jurgen
Author_Institution
Res. Inst. for Nanodevice & Bio Syst., Hiroshima Univ., Hiroshima, Japan
fYear
2013
fDate
16-20 Sept. 2013
Firstpage
267
Lastpage
270
Abstract
The reported digital, word-parallel and scalable coprocessor architecture for nearest Euclidean distance (ED) search is based on mapping the distance into time domain onto an equivalent clock number. Area-efficient sequential square calculation and a minimization algorithm of the clock number necessary for the search are applied for practical efficiency. Experimental concept verification was done with an 180nm CMOS design implementing 32 reference vectors with 16 components and 8 bit per component. The fabricated test chips achieved 1.19μs average search time, 5.77 μs worst-case search time and low power dissipation of 8.75mW at 47MHz and Vdd=1.8V for code-book-based picture compression. To our best knowledge this is the first report of practical, word-parallel, digital nearest ED-search architecture. In comparison to previous digital-analog ASIC and GPU implementations, factors 1.8 and 4.5·105 smaller power delay products per 1NN search are realized, respectively.
Keywords
CMOS integrated circuits; coprocessors; pattern matching; vectors; codebook-based picture compression; digital nearest ED-search architecture; digital word-parallel scalable coprocessor architecture; equivalent clock number; frequency 47 MHz; minimization algorithm; nearest Euclidean distance search; power 8.75 mW; sequential square calculation; size 180 nm; time domain; voltage 1.8 V; CMOS integrated circuits; Clocks; Coprocessors; Data compression; Euclidean distance; Radiation detectors; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
ESSCIRC (ESSCIRC), 2013 Proceedings of the
Conference_Location
Bucharest
ISSN
1930-8833
Print_ISBN
978-1-4799-0643-7
Type
conf
DOI
10.1109/ESSCIRC.2013.6649124
Filename
6649124
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