Name
Abstract | ||
|---|---|---|
We propose a novel and efficient incremental analysis technique for 'what-if analysis of on-chip power distribution networks (PDN). Effect of local modifications to a PDN, including local topology changes, can be quickly analyzed without need for very expensive re-analysis of the entire modified network. We borrow ideas from a fictitious domain method that has been successfully used in solving partial differential equations arising from inhomogeneous problems in mechanics. The effect of local wiring modifications in several PDN regions is mimicked by applying fictitious currents at the boundaries of these regions in the original unmodified network. The fictitious currents are calculated from component sub-problems in a low-computation iterative procedure. The practicality of this method for use in what-if analysis is demonstrated with several large power networks from actual industrial designs. It analyzes a modified network with few million changes in a fraction of time it would take for a complete re-analysis. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICCAD.2007.4397366 | ICCAD |
Keywords | Field | DocType |
novel technique,pdn region,entire modified network,on-chip power distribution network,local wiring modification,large power network,what-if analysis,fictitious current,efficient incremental analysis technique,local modification,fictitious domain method,local topology change,partial differential equation,low power electronics,decoupling capacitors,partial differential equations,iterative methods,chip,industrial design | Computer science,Iterative method,Distribution networks,Fictitious domain method,Electronic engineering,Decoupling capacitor,Power noise,Partial differential equation,Low-power electronics | Conference |
ISSN | ISBN | Citations |
1063-6757 | 1-4244-1382-6 | 6 |
PageRank | References | Authors |
0.51 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhong Fu | 1 | 83 | 7.51 |
| R. Panda | 2 | 1002 | 111.69 |
| Ben Reschke | 3 | 13 | 1.16 |
| Savithri Sundareswaran | 4 | 190 | 16.84 |
| Min Zhao | 5 | 88 | 7.56 |