5 papers
NN-PARS: A Parallelized Neural Network Based Circuit Simulation Framework
Mohammad Saeed Abrishami, Hao Ge, Justin F. Calderon +2
The shrinking of transistor geometries as well as the increasing complexity of integrated circuits, significantly aggravate nonlinear design behavior. This demands accurate and fas…
CSM-NN: Current Source Model Based Logic Circuit Simulation -- A Neural Network Approach
Mohammad Saeed Abrishami, Massoud Pedram, Shahin Nazarian
The miniaturization of transistors down to 5nm and beyond, plus the increasing complexity of integrated circuits, significantly aggravate short channel effects, and demand analysis…
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen +3
Recent advances in the field of artificial intelligence have been made possible by deep neural networks. In applications where data are scarce, transfer learning and data augmentat…
A Meta-Learning Approach for Custom Model Training
Amir Erfan Eshratifar, Mohammad Saeed Abrishami, David Eigen +1
Transfer-learning and meta-learning are two effective methods to apply knowledge learned from large data sources to new tasks. In few-class, few-shot target task settings (i.e. whe…
JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services
Amir Erfan Eshratifar, Mohammad Saeed Abrishami, Massoud Pedram
Deep learning models are being deployed in many mobile intelligent applications. End-side services, such as intelligent personal assistants, autonomous cars, and smart home service…