Name
Title | ||
|---|---|---|
Application of a novel evolutionary neural network for macro-cell placement optimization in VLSI physical design |
Abstract | ||
|---|---|---|
As operation frequencies and integration densities of modern very large-scale integration (VLSI) circuits increase while device sizes shrink, the quest for high-speed VLSI applications has highlighted the negligible effects of interconnects. It is important to minimize the interconnect wire lengths during VLSI physical design stage. This paper focuses on the minimization process of the total wire length after placement, that is, macro-cell orientation. A novel evolutionary neural network approach based on the concept of evolutionary programming (EPENN) is proposed to address this combinatorial optimization problem. Numerical experiments and simulation results have shown that the presented approach can obtain high quality solutions with low computational complexity. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11816157_77 | ICIC (1) |
Keywords | Field | DocType |
combinatorial optimization problem,large-scale integration,vlsi physical design stage,novel evolutionary neural network,circuits increase,evolutionary programming,wire length,macro-cell placement optimization,integration density,total wire length,high-speed vlsi application,computational complexity | Evolutionary algorithm,Computer science,Circuit design,Algorithm,Combinatorial optimization,Artificial neural network,Interconnection,Evolutionary programming,Very-large-scale integration,Computer engineering,Distributed computing,Computational complexity theory | Conference |
Volume | ISSN | ISBN |
4113 | 0302-9743 | 3-540-37271-7 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Zhou | 1 | 1 | 0.73 |
| Gaofeng Wang | 2 | 24 | 10.09 |
| Xi Chen | 3 | 68 | 7.51 |