Imbalance aware lithography hotspot detection: a deep learning approach

H Yang, L Luo, J Su, C Lin, B Yu - Journal of Micro …, 2017 - spiedigitallibrary.org
With the advancement of very large scale integrated circuits (VLSI) technology nodes,
lithographic hotspots become a serious problem that affects manufacture yield. Lithography …

Design for manufacturability and reliability in extreme-scaling VLSI

B Yu, X Xu, S Roy, Y Lin, J Ou, DZ Pan - Science China Information …, 2016 - Springer
In the last five decades, the number of transistors on a chip has increased exponentially in
accordance with the Moore's law, and the semiconductor industry has followed this law as …

Accurate lithography hotspot detection using deep convolutional neural networks

M Shin, JH Lee - Journal of Micro/Nanolithography, MEMS …, 2016 - spiedigitallibrary.org
As the physical design of semiconductors continues to shrink, the lithography process is
becoming more sensitive to layout design. Identifying lithography hotspots (HSs) in the …

Faster region-based hotspot detection

R Chen, W Zhong, H Yang, H Geng, X Zeng… - Proceedings of the 56th …, 2019 - dl.acm.org
As the circuit feature size continuously shrinks down, hotspot detection has become a more
challenging problem in modern DFM flows. Developed deep learning techniques have …

Hotspot detection via attention-based deep layout metric learning

H Geng, H Yang, L Zhang, J Miao, F Yang… - Proceedings of the 39th …, 2020 - dl.acm.org
With the aggressive and amazing scaling of the feature size of semiconductors, hotspot
detection has become a crucial and challenging problem in the generation of optimized …

Applications of VLSI Design in Artificial Intelligence and Machine Learning

IU Khan, N Mittal, MA Ansari - Machine Learning for VLSI Chip …, 2023 - Wiley Online Library
In our advanced times, complementary metal‐oxide semiconductor (CMOS) based
organizations like semiconductor and gadgets face extreme scheduling of products and …

Lithography hotspot detection: From shallow to deep learning

H Yang, Y Lin, B Yu, EFY Young - 2017 30th IEEE International …, 2017 - ieeexplore.ieee.org
As VLSI technology nodes continue, the gap between lithography system manufacturing
ability and transistor feature size induces serious problems, thus lithography hotspot …

Semi-supervised hotspot detection with self-paced multi-task learning

Y Chen, Y Lin, T Gai, Y Su, Y Wei, DZ Pan - … of the 24th Asia and South …, 2019 - dl.acm.org
Lithography simulation is computationally expensive for hotspot detection. Machine learning
based hotspot detection is a promising technique to reduce the simulation overhead …

Machine learning and pattern matching in physical design

B Yu, DZ Pan, T Matsunawa… - The 20th Asia and South …, 2015 - ieeexplore.ieee.org
Machine learning (ML) and pattern matching (PM) are powerful computer science
techniques which can derive knowledge from big data, and provide prediction and matching …

Automatic layout feature extraction for lithography hotspot detection based on deep neural network

T Matsunawa, S Nojima… - … -Process-Technology Co …, 2016 - spiedigitallibrary.org
Lithography hotspot detection in the physical verification phase is one of the most important
techniques in today's optical lithography based manufacturing process. Although lithography …