MLCAD: A survey of research in machine learning for CAD keynote paper
Due to the increasing size of integrated circuits (ICs), their design and optimization phases
(ie, computer-aided design, CAD) grow increasingly complex. At design time, a large design …
(ie, computer-aided design, CAD) grow increasingly complex. At design time, a large design …
The policy-gradient placement and generative routing neural networks for chip design
Placement and routing are two critical yet time-consuming steps of chip design in modern
VLSI systems. Distinct from traditional heuristic solvers, this paper on one hand proposes an …
VLSI systems. Distinct from traditional heuristic solvers, this paper on one hand proposes an …
GeniusRoute: A new analog routing paradigm using generative neural network guidance
Due to sensitive layout-dependent effects and varied performance metrics, analog routing
automation for performance-driven layout synthesis is difficult to generalize. Existing …
automation for performance-driven layout synthesis is difficult to generalize. Existing …
Understanding graphs in EDA: From shallow to deep learning
As the scale of integrated circuits keeps increasing, it is witnessed that there is a surge in the
research of electronic design automation (EDA) to make the technology node scaling …
research of electronic design automation (EDA) to make the technology node scaling …
Computational lithography using machine learning models
Y Shin - IPSJ Transactions on System and LSI Design …, 2021 - jstage.jst.go.jp
Machine learning models have been applied to a wide range of computational lithography
applications since around 2010. They provide higher modeling capability, so their …
applications since around 2010. They provide higher modeling capability, so their …
Flowtune: Practical multi-armed bandits in boolean optimization
C Yu - Proceedings of the 39th International Conference on …, 2020 - dl.acm.org
Recent years have seen increasing employment of decision intelligence in electronic design
automation (EDA), which aims to reduce the manual efforts and boost the design closure …
automation (EDA), which aims to reduce the manual efforts and boost the design closure …
Decision making in synthesis cross technologies using lstms and transfer learning
We propose a general approach that precisely estimates the Quality-of-Result (QoR), such
as delay and area, of unseen synthesis flows for specific designs. The main idea is …
as delay and area, of unseen synthesis flows for specific designs. The main idea is …
Diffpattern: Layout pattern generation via discrete diffusion
Deep generative models dominate the existing literature in layout pattern generation.
However, leaving the guarantee of legality to an inexplicable neural network could be …
However, leaving the guarantee of legality to an inexplicable neural network could be …
Layoutransformer: Generating layout patterns with transformer via sequential pattern modeling
Generating legal and diverse layout patterns to establish large pattern libraries is
fundamental for many lithography design applications. Existing pattern generation models …
fundamental for many lithography design applications. Existing pattern generation models …
Label-free neural networks-based inverse lithography technology
Neural network-based inverse lithography technology (NNILT) has been used to improve
the computational efficiency of large-scale mask optimization for advanced …
the computational efficiency of large-scale mask optimization for advanced …