DocumentCode
500821
Title
PiCAP: A parallel and incremental capacitance extraction considering stochastic process variation
Author
Gong, Fang ; Yu, Hao ; He, Lei
Author_Institution
EE Dept., UCLA, Los Angeles, CA, USA
fYear
2009
fDate
26-31 July 2009
Firstpage
764
Lastpage
769
Abstract
It is unknown how to include stochastic process variation into fast multipole method (FMM) for a full chip capacitance extraction. This paper presents a parallel FMM extraction using stochastic polynomial expanded geometrical moments. It utilizes multiprocessors to evaluate in parallel for the stochastic potential interaction and its matrix vector product (MVP) with charge. Moreover, a generalized minimal residual (GMRES) method with deflation is modified to incrementally consider the nominal value and the variance. The overall extraction flow is called piCAP. Experiments show that the parallel MVP in piCAP is up to 3X faster than the serial MVP, and the incremental GMRES in pi-CAP is up to 15X faster than non-incremental GMRES methods.
Keywords
integrated circuit design; stochastic processes; GMRES method; expanded geometrical moment; generalized minimal residual method; incremental capacitance extraction; matrix vector product; multiprocessor system; nominal value; parallel FMM extraction; parallel capacitance extraction; parallel fast multipole method extraction; stochastic polynomial; stochastic potential interaction; stochastic process variation; Algorithm design and analysis; Capacitance; Computational efficiency; Design automation; Dielectrics; Helium; Matrix decomposition; Permission; Polynomials; Stochastic processes; Capacitance extraction; Incremental precondition; Parallel fast-multipole method; Stochastic geometrical moments;
fLanguage
English
Publisher
ieee
Conference_Titel
Design Automation Conference, 2009. DAC '09. 46th ACM/IEEE
Conference_Location
San Francisco, CA
ISSN
0738-100X
Print_ISBN
978-1-6055-8497-3
Type
conf
Filename
5227077
Link To Document