64 citations · 256 across the 76 of their papers we have counts for
4 papers · 1 filter
Pre-Defined Sparse Neural Networks with Hardware Acceleration
Sourya Dey, Kuan-Wen Huang, Peter A. Beerel +1
Neural networks have proven to be extremely powerful tools for modern artificial intelligence applications, but computational and storage complexity remain limiting factors. This p…
SpRRAM: A Predefined Sparsity Based Memristive Neuromorphic Circuit for Low Power Application
Arash Fayyazi, Souvik Kundu, Shahin Nazarian +2
In this paper, we propose an efficient predefined structured sparsity-based ex-situ training framework for a hybrid CMOS-memristive neuromorphic hardware for deep neural network to…
Morse Code Datasets for Machine Learning
Sourya Dey, Keith M. Chugg, Peter A. Beerel
We present an algorithm to generate synthetic datasets of tunable difficulty on classification of Morse code symbols for supervised machine learning problems, in particular, neural…
A Highly Parallel FPGA Implementation of Sparse Neural Network Training
Sourya Dey, Diandian Chen, Zongyang Li +4
We demonstrate an FPGA implementation of a parallel and reconfigurable architecture for sparse neural networks, capable of on-chip training and inference. The network connectivity…