DocumentCode :
3376855
Title :
The fast optimal voltage partitioning algorithm for peak power density minimization
Author :
Wang, Jia ; Hu, Shiyan
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Technol. Univ., Houghton, MI, USA
fYear :
2010
fDate :
7-11 Nov. 2010
Firstpage :
213
Lastpage :
217
Abstract :
Increasing transistor density in nanometer integrated circuits has resulted in large on-chip power density. As a high-level power optimization technique, voltage partitioning is effective in mitigating power density. Previous works on voltage partitioning attempt to address it through minimizing total power consumption over all voltage partitions. Since power density significantly impacts thermal-induced reliability, it is also desired to directly mitigate peak power density during voltage partitioning. Unfortunately, none of the existing works consider this. This paper proposes an efficient optimal voltage partitioning algorithm for peak power density minimization. Based on novel algorithmic techniques such as implicit power density binary search, the algorithm runs in O(n log n + m2 log2 n) time, where n refers to the number of functional units and m refers to the number of partitions/voltage levels. Our experimental results on large testcases demonstrate that large amount of (about 9.7×) reduction in peak power density can be achieved compared to a natural greedy algorithm, while the algorithm still runs very fast. It needs only 14.15 seconds to optimize 1M functional units.
Keywords :
circuit optimisation; integrated circuit design; nanotechnology; fast optimal voltage partitioning algorithm; high level power optimization technique; implicit power density binary search; nanometer integrated circuit; peak power density minimization; transistor density; Algorithm design and analysis; Binary search trees; Capacitance; Greedy algorithms; Minimization; Partitioning algorithms; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Design (ICCAD), 2010 IEEE/ACM International Conference on
Conference_Location :
San Jose, CA
ISSN :
1092-3152
Print_ISBN :
978-1-4244-8193-4
Type :
conf
DOI :
10.1109/ICCAD.2010.5654144
Filename :
5654144
Link To Document :
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