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Found 17 papers, 3 papers with code
CAMO: Correlation-Aware Mask Optimization with Modulated Reinforcement Learning
Optical proximity correction (OPC) is a vital step to ensure printability in modern VLSI manufacturing.
Optimizing Predictive AI in Physical Design Flows with Mini Pixel Batch Gradient Descent
Exploding predictive AI has enabled fast yet effective evaluation and decision-making in modern chip physical design flows.
GPU-accelerated Matrix Cover Algorithm for Multiple Patterning Layout Decomposition
Multiple patterning lithography (MPL) is regarded as one of the most promising ways of overcoming the resolution limitations of conventional optical lithography due to the delay of next-generation lithography technology.
Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields
Lithography is fundamental to integrated circuit fabrication, necessitating large computation overhead.
Entity Aware Modelling: A Survey
However, these entity characteristics are not readily available in many real-world scenarios, and different ML methods have been proposed to infer these characteristics from the data.
Transfer learning for process design with reinforcement learning
We thus propose to utilize transfer learning for process design with RL in combination with rigorous simulation methods.
An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design
These synthetic mask images will augment the original limited training dataset used to finetune the lithography model for improved performance.
Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training
Machine learning techniques have been extensively studied for mask optimization problems, aiming at better mask printability, shorter turnaround time, better mask manufacturability, and so on.
Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks
Lithography simulation is a critical step in VLSI design and optimization for manufacturability.
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature
However, the information of released water flow is often not available for many reservoirs, which makes it difficult for data-driven models to capture the impact to downstream river segments.
ROS-X-Habitat: Bridging the ROS Ecosystem with Embodied AI
We introduce ROS-X-Habitat, a software interface that bridges the AI Habitat platform for embodied learning-based agents with other robotics resources via ROS.
Routing Towards Discriminative Power of Class Capsules
The activation of lower layer capsules affects the behavior of the following capsules via routing links that are constructed during training via certain routing algorithms.
Machine Learning for Electronic Design Automation: A Survey
With the down-scaling of CMOS technology, the design complexity of very large-scale integrated (VLSI) is increasing.
Incorporating Causal Effects into Deep Learning Predictions on EHR Data
Electronic Health Records (EHR) data analysis plays a crucial role in healthcare system quality.
VLSI Mask Optimization: From Shallow To Deep Learning
VLSI mask optimization is one of the most critical stages in manufacturability aware design, which is costly due to the complicated mask optimization and lithography simulation.
Automatic Layout Generation with Applications in Machine Learning Engine Evaluation
The tool currently supports both metal layer and via layer generation.
Bridging the Gap Between Layout Pattern Sampling and Hotspot Detection via Batch Active Sampling
Layout hotpot detection is one of the main steps in modern VLSI design.
