DocumentCode :
3037484
Title :
Clustered Multi-dictionary Code Compression for Embedded Systems
Author :
Ji Tu ; MeiSong Zheng ; Zilong Wang ; Lijian Li ; Junye Wang
Author_Institution :
Inst. of Autom., Beijing, China
fYear :
2015
fDate :
7-9 April 2015
Firstpage :
473
Lastpage :
473
Abstract :
A novel clustered multi-dictionary code compression method is proposed to effectively reduce the memory size which program code stored. According to the repeat times of distinct codes, the code set is clustered into several clusters. Each cluster is compressed with different dictionary and the codeword length is the same for the same dictionary. Shorter codeword is used for the dictionary whose size is smaller. Experimental results of MiBench benchmark compiled for ARM and MIPS show that the compression efficiency of this method is superior to the traditional multi-level dictionary-based code compression. The latency of instruction fetch is almost not increased, decode logic overhead is tiny and acceptable. Furthermore, the storage-bandwidth is increased.
Keywords :
data compression; embedded systems; ARM; clustered multidictionary code compression method; code set; codeword length; compression efficiency; decode logic overhead; embedded systems; instruction fetch latency; memory size; multilevel dictionary-based code compression; program code; storage bandwidth; Adaptive systems; Automation; Benchmark testing; Clustering algorithms; Data compression; Dictionaries; Embedded systems; cluster; code compression; embedded systems; memory architecture; multi-dictionary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Compression Conference (DCC), 2015
Conference_Location :
Snowbird, UT
ISSN :
1068-0314
Type :
conf
DOI :
10.1109/DCC.2015.6
Filename :
7149336
Link To Document :
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