Routability Optimization for Industrial Designs at Sub-14nm Process Nodes Using Machine Learning
Author:
Affiliation:
1. University of California, San Diego, La Jolla, CA, USA
2. Synopsys Inc., Hillsboro, OR, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3036669.3036681
Reference32 articles.
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2. An effective congestion driven placement framework
3. On wirelength estimations for row-based placement
4. BEOL stack-aware routability prediction from placement using data mining techniques
5. Hierarchical whitespace allocation in top-down placement
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