loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
7th International Symposium on Quality Electronic Design (ISQED'06)
SMM: Scalable Analysis of Power Delivery Networks by Stochastic Moment Matching
San Jose, California
March 27-March 29
ISBN: 0-7695-2523-7
Andrew B. Kahng, UC San Diego
Bao Liu, UC San Diego
Sheldon Tan, UC Riverside
This paper proposes a novel method for analyzing large onchip power delivery networks via a stochastic moment matching (SMM) method. The proposed method extends the existing direct stochastic random walk method that can be only applied to DC analysis in purely resistive networks or transient analysis of RC networks with low efficiency. The new method can analyze general structure RLC networks by combining the stochastic process with frequency domain moment matching technique. As a result, we achieve better scalability than traditional frequency domain P/G analysis approaches, and better efficiency than existing random walk transient analysis techniques. Our experimental results show that SMM can easily trade efficiency for accuracy or vise versa. SMM can easily deliver 10X-100X speedup over a LU-based direct solver and about 10X speedup over the pure random walk method with reasonable accuracy on large industry P/G networks.
Citation:
Andrew B. Kahng, Bao Liu, Sheldon Tan, "SMM: Scalable Analysis of Power Delivery Networks by Stochastic Moment Matching," isqed, pp.638-643, 7th International Symposium on Quality Electronic Design (ISQED'06), 2006
Usage of this product signifies your acceptance of the Terms of Use.