DocumentCode
34041
Title
Efficient Transient Analysis of Power Delivery Network With Clock/Power Gating by Sparse Approximation
Author
Zhu, H. ; Wang, Y. ; Liu, F. ; Li, X. ; Zeng, X. ; Feldmann, P.
Author_Institution
Microelectronics DepartmentState Key Laboratory of ASIC & System, Fudan University, Shanghai, China
Volume
34
Issue
3
fYear
2015
fDate
Mar-15
Firstpage
409
Lastpage
421
Abstract
Transient analysis of large-scale power delivery network (PDN) is a critical task to ensure the functional correctness and desired performance of today’s integrated circuits (ICs), especially if significant transient noises are induced by clock and/or power gating due to the utilization of extensive power management. In this paper, we propose an efficient algorithm for PDN transient analysis based on sparse approximation. The key idea is to exploit the fact that the transient response caused by clock/power gating is often localized and the voltages at many other “inactive” nodes are almost unchanged, thereby rendering a unique sparse structure. By taking advantage of the underlying sparsity of the solution structure, a modified conjugate gradient algorithm is developed and tuned to efficiently solve the PDN analysis problem with low computational cost. Our numerical experiments based on standard benchmarks demonstrate that the proposed transient analysis with sparse approximation offers up to
runtime speedup over other traditional methods, while simultaneously achieving similar accuracy.
Keywords
Algorithm design and analysis; Approximation methods; Clocks; Equations; Mathematical model; Transient analysis; Vectors; Conjugate gradient (CG); Power delivery network; conjugate gradient; orthogonal matching pursuit; orthogonal matching pursuit (OMP); power delivery network (PDN); sparse approximation; transient analysis;
fLanguage
English
Journal_Title
Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0278-0070
Type
jour
DOI
10.1109/TCAD.2015.2391256
Filename
7018900
Link To Document