DocumentCode :
1145378
Title :
ENPCO: an entropy-based partition-codec algorithm to reduce power for bipartition-codec architecture in pipelined circuits
Author :
Ruan, Shanq-Jang ; Naroska, Edwin ; Chang, Yen-Jen ; Lai, Feipei ; Schwiegelshohn, Uwe
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Volume :
10
Issue :
6
fYear :
2002
Firstpage :
942
Lastpage :
949
Abstract :
This work proposes a new algorithm to synthesize low power bipartition-codec architecture for pipelined circuits. The bipartition-codec architecture has been introduced as an effective power reduction technique for circuit design. The entropy-based partition-codec (ENPCO) algorithm extends this approach as it optimizes for both: power and area. It uses entropy as a criterion to balance between power and area. The ENPCO algorithm is composed of two phases: first, it clusters the output vectors with high occurrence into a group, moving all remaining output vectors into another group. The first group will be encoded in order to save power. Secondly, based on circuit entropy, output patterns are moved between both groups in order to balance power consumption and area overhead. A number of Microelectronic Center of North Carolina (MCNC) benchmarks were used to verify the effectiveness of our algorithm. Results demonstrate that ENPCO algorithm can achieve low power with less area overhead than the single-phase algorithm introduced previously by Shanq-Jang Ruan et al. (1999).
Keywords :
VLSI; circuit CAD; circuit optimisation; circuit simulation; codecs; computational complexity; digital signal processing chips; entropy; high level synthesis; integrated circuit design; low-power electronics; pipeline processing; ENPCO; VLSI chip design; area optimization; bipartition-codec architecture; circuit entropy; complexity analysis; entropy-based partition-codec algorithm; low power codec architecture synthesis; output vectors clustering; pipelined circuits; power optimization; power reduction technique; Circuit synthesis; Clustering algorithms; Computer science; Energy consumption; Entropy; Partitioning algorithms; Pipeline processing; Power dissipation; Power engineering computing; Very large scale integration;
fLanguage :
English
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-8210
Type :
jour
DOI :
10.1109/TVLSI.2002.808422
Filename :
1178865
Link To Document :
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