Sponsor: Intelligence Advanced Research Projects Activity (IARPA)
we address the problem of deriving a functional description of a circuit from an unstructured netlist by leveraging deep learning and circuit representations based on convolutional neural networks (CNNs). In doing so, we are motivated by the state-of-the-art performance of machine learning (ML) techniques, based on both convolutional and deep neural networks, for solving challenging problems including classification, pattern recognition, language processing, and decision making in a variety of applications – from business, to social work, medicine, and engineering.Related work:
- A. Fayyazi, S. Shababi, P. Nuzzo, S. Nazarian, and M. Pedram, “Deep Learning-Based Circuit Recognition Using Sparse Mapping anf Level-Dependent Decaaying Sum Circuit Representations,” to appear in DATE 2019.