DocumentCode
2546504
Title
Efficient Second-Order Iterative Methods for IR Drop Analysis in Power Grid
Author
Zhong, Yu ; Wong, Martin D F
Author_Institution
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL
fYear
2007
fDate
23-26 Jan. 2007
Firstpage
768
Lastpage
773
Abstract
Due to the extremely large sizes of power grids, IR drop analysis has become a computationally challenging problem both in terms of runtime and memory usage. It has been shown in (Zhong and Wong, 2005) that first-order iterative algorithms based on node-by-node and row-by-row traversals of the power grid have both accuracy and runtime advantages over the well-known random-walk method. In this paper, we propose second-order iterative algorithms that can significantly reduce the runtime. The new algorithms are extremely fast, and we prove that they guarantee converge to the exact solutions. Experimental results show that our algorithms outperform the random-walk algorithm in (Qian et al., 2003) and algorithms in (Zhong and Wong, 2005), For a 25-million node problem, while the random-walk algorithm takes 2 days with maximum error of 6.1 mV, the fastest algorithm in (Zhong and Wong, 2005) takes 50 minutes, and our second-order row-based algorithm takes 32 minutes to get an exact solution. Moreover, we can get a solution with maximum error 2 mV in 10 minutes.
Keywords
integrated circuit design; iterative methods; power grids; 10 mins; 2 mV; 32 mins; 50 mins; 6.1 mV; IR drop analysis; first-order iterative algorithms; node-by-node traversals; power grid; random-walk method; row-by-row traversals; second-order iterative methods; Circuits; Convergence; Grid computing; Iterative algorithms; Iterative methods; Optical computing; Power engineering and energy; Power engineering computing; Power grids; Runtime;
fLanguage
English
Publisher
ieee
Conference_Titel
Design Automation Conference, 2007. ASP-DAC '07. Asia and South Pacific
Conference_Location
Yokohama
Print_ISBN
1-4244-0629-3
Electronic_ISBN
1-4244-0630-7
Type
conf
DOI
10.1109/ASPDAC.2007.358082
Filename
4196128
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