Prediction of process-sensitive geometries with machine learning
US10402524B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 8, 2017 |
| Grant date | Sep 3, 2019 |
| Priority date | — |
| Expiry date | Jun 6, 2037 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods according to the disclosure include: predicting process-sensitive geometries (PSGs) in a proposed IC layout based on violations of a set of processing constraints for the proposed IC layout, the set of processing constraints being calculated with a predictive model based on a training data repository having a plurality of optical rule check (ORC) simulations for different IC layouts; identifying actual PSGs in a circuit manufactured using the proposed IC layout; determining whether the predicted PSGs correspond to the actual PSGs in the manufactured circuit as being correct; in response to the predicting being incorrect: adjusting the predictive model based on the actual PSGs, wherein the adjusting includes submitting additional ORC data to the training data repository; and flagging the proposed IC layout as incorrectly predicted; and in response to the predicting being correct, flagging the proposed IC layout as correctly predicted.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.