A novel clustered multi-dictionary code compression method

Code compression is traditionally used to reduce the code size by compressing the codes with higher static frequency. A novel clustered multi-dictionary code compression method is proposed to effectively reduce the memory size which program code stored. We cluster the code set according to the repeat times frequency of different codes in it. Each cluster is compressed with different dictionary and the codeword of each cluster is different. We use shorter codeword to point to the more frequently occurred codes in cluster. By finding the best clusters, the entropy of clustered multi-dictionary code is high and the compression efficiency is the best. Theoretical proof and experimental results show that the compression effect of this method is significant. Code of MiBench benchmark compiled under ARM and MIPS instruction set architecture are compressed with this method and the best compression ratio is 50%.