DocumentCode
3265606
Title
A novel power estimation framework for SRAM-based FPGAs
Author
Wang, Shuo ; Chen, Lei ; Wen, Zhiping ; Chu, Peng ; Wang, Lei
Author_Institution
Dept. Design, Beijing Microelectron. Tech. Instn. (BMTI), Beijing, China
fYear
2009
fDate
19-21 Jan. 2009
Firstpage
444
Lastpage
447
Abstract
Field programmable gate arrays (FPGAs) is becoming one of the most widely used electronics devices. Because of its unique architecture, power estimation is a complicated task for FPGAs. This paper presents a novel power estimation framework for SRAM-based FPGAs. Considering both dynamic power and static power, a gate-level power model for configuration logic blocks (CLBs) and a transistor-level power model for interconnect resources is developed for power estimation of SRAM-based FPGAs. To achieve the accuracy and efficiency, we use the transition density method includes glitches filtering in our proposed power estimation framework. 20 MCNC benchmark circuits have been applied to our proposed power estimation framework, and the detailed power dissipation distribution obtained from the experimental results is presented. The proposed framework is also quite flexible, which is capable of estimating power for a wide variety of SRAM-based FPGA architectures.
Keywords
SRAM chips; field programmable gate arrays; logic design; MCNC benchmark circuits; SRAM-based FPGA; configuration logic block; dynamic power; field programmable gate array; gate-level power model; glitches filtering; power dissipation distribution; power estimation; static power; transistor-level power model; transition density method; Application specific integrated circuits; Electronic mail; Energy consumption; Field programmable gate arrays; Integrated circuit interconnections; Logic devices; Low pass filters; Microelectronics; Power dissipation; Programmable logic arrays;
fLanguage
English
Publisher
ieee
Conference_Titel
Microelectronics & Electronics, 2009. PrimeAsia 2009. Asia Pacific Conference on Postgraduate Research in
Conference_Location
Shanghai
Print_ISBN
978-1-4244-4668-1
Electronic_ISBN
978-1-4244-4669-8
Type
conf
DOI
10.1109/PRIMEASIA.2009.5397349
Filename
5397349
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