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CSM-NN: Current Source Model Based Logic Circuit Simulation -- A Neural Network Approach
The miniaturization of transistors down to 5nm and beyond, plus the increasing complexity of integrated circuits, significantly aggravate short channel effects, and demand analysis and optimization of more design corners and modes.
NN-PARS: A Parallelized Neural Network Based Circuit Simulation Framework
The shrinking of transistor geometries as well as the increasing complexity of integrated circuits, significantly aggravate nonlinear design behavior.
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
However, fine-tuning a transfer model with data augmentation in the raw input space has a high computational cost to run the full network for every augmented input.
A Meta-Learning Approach for Custom Model Training
Transfer-learning and meta-learning are two effective methods to apply knowledge learned from large data sources to new tasks.
JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services
Deep learning models are being deployed in many mobile intelligent applications.
