GRASP based Metaheuristics for Layout Pattern Classification
- Title
- GRASP based Metaheuristics for Layout Pattern Classification
- Authors
- Woo, Mangy; Kim, Seungwon; KANG, SEOKHYEONG
- Date Issued
- 2017-11-15
- Publisher
- IEEE/ACM
- Abstract
- Layout pattern classification has been recently utilized in IC design. It clusters hotspot patterns for design-space analysis or yield optimization. In pattern classification, an optimal clustering is essential, as well as its runtime and accuracy. Within the research-oriented infrastructure used in the ICCAD 2016 contest, we have developed a fast metaheuristic for the pattern classification that utilizes the Greedy Randomized Adaptive Search Procedure (GRASP). Our proposed metaheuristic outperforms the best-reported results on all of the ICCAD 2016 benchmarks. In addition, we achieve up to a 50% cluster count reduction, and improve a runtime significantly compared to a commercial EDA tool provided in the ICCAD 2016 contest [1].
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/98417
- Article Type
- Conference
- Citation
- International Conference on Computer-Aided Design, 2017-11-15
- Files in This Item:
- There are no files associated with this item.
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