DocumentCode :
3706131
Title :
A low-energy ASIP with flexible exponential Golomb codec for lossless data compression toward artificial vision systems
Author :
Tomoki Sugiura;Jaehoon Yu;Yoshinori Takeuchi;Masaharu Imai
Author_Institution :
Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan
fYear :
2015
Firstpage :
1
Lastpage :
4
Abstract :
This paper proposes an application-domain specific instruction-set processor (ASIP) with dedicated instructions for lossless data compression and decompression process to be used in artificial vision systems. Proposed ASIP has dedicated instructions to accelerate the performance to codec operations of Exponential Golomb coding, where the coding parameter value can be set by the user in order to maximize the compression ratio. Experimental results through simulation show that the proposed ASIP reduces execution cycles by 88% for compression and 42% for decompression, and reduces energy consumption by 85% for compression and 40% for decompression, compared with the base reduced instruction set computer processor.
Keywords :
"Codecs","Encoding","Yttrium","Machine vision","Logic gates","Data compression","Energy consumption"
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE
Type :
conf
DOI :
10.1109/BioCAS.2015.7348302
Filename :
7348302
Link To Document :
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