| Autor: |
Francisco, Luis, Lagare, Tanmay, Jain, Arpit, Chaudhary, Somal, Kulkarni, Madhura, Sardana, Divya, Davis, W. Rhett, Franzon, Paul |
| Rok vydání: |
2020 |
| Předmět: |
|
| Druh dokumentu: |
Working Paper |
| Popis: |
Design rule checking (DRC) is getting increasingly complex in advanced nodes technologies. It would be highly desirable to have a fast interactive DRC engine that could be used during layout. In this work, we establish the proof of feasibility for such an engine. The proposed model consists of a convolutional neural network (CNN) trained to detect DRC violations. The model was trained with artificial data that was derived from a set of $50$ SRAM designs. The focus in this demonstration was metal 1 rules. Using this solution, we can detect multiple DRC violations 32x faster than Boolean checkers with an accuracy of up to 92. The proposed solution can be easily expanded to a complete rule set. |
| Databáze: |
arXiv |
| Externí odkaz: |
|
