DocumentCode :
2156110
Title :
Structure-aware high-dimensional performance modeling for analog and mixed-signal circuits
Author :
Shupeng Sun ; Xin Li ; Chenjie Gu
Author_Institution :
Electr. & Comput. Eng. Dept., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2013
fDate :
22-25 Sept. 2013
Firstpage :
1
Lastpage :
4
Abstract :
Efficient high-dimensional performance modeling of nanoscale analog and mixed signal (AMS) circuits is extremely challenging. In this paper, we propose a novel structure-aware modeling (SAM) technique. The key idea of SAM is to accurately solve the model coefficients by applying an efficient statistical algorithm to exploit the underlying structure of AMS circuits. As a result, SAM dramatically reduces the required number of sampling points and, hence, the computational cost for performance modeling. Several circuit examples designed in a commercial 32nm CMOS process demonstrate that SAM achieves more than 2× runtime speedup over the traditional sparse regression technique without surrendering any accuracy.
Keywords :
CMOS integrated circuits; analogue integrated circuits; integrated circuit modelling; mixed analogue-digital integrated circuits; CMOS process; analog circuits; mixed-signal circuits; size 32 nm; statistical algorithm; structure-aware high-dimensional performance modeling; Computational modeling; Correlation; Integrated circuit modeling; Performance evaluation; Semiconductor device modeling; Solid modeling; Transistors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Custom Integrated Circuits Conference (CICC), 2013 IEEE
Conference_Location :
San Jose, CA
Type :
conf
DOI :
10.1109/CICC.2013.6658463
Filename :
6658463
Link To Document :
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