221 citations · 405 across the 27 of their papers we have counts for
5 papers · 1 filter
An Inference and Learning Engine for Spiking Neural Networks in Computational RAM (CRAM)
Hüsrev Cılasun, Salonik Resch, Zamshed I. Chowdhury +8
Spiking Neural Networks (SNN) represent a biologically inspired computation model capable of emulating neural computation in human brain and brain-like structures. The main promise…
Molecular MUX-Based Physical Unclonable Functions
Lulu Ge, Keshab K. Parhi
Physical unclonable functions (PUFs) are small circuits that are widely used as hardware security primitives for authentication. These circuits can generate unique signatures becau…
PERMDNN: Efficient Compressed DNN Architecture with Permuted Diagonal Matrices
Chunhua Deng, Siyu Liao, Yi Xie +3
Deep neural network (DNN) has emerged as the most important and popular artificial intelligent (AI) technique. The growth of model size poses a key energy efficiency challenge for…
Classification using Hyperdimensional Computing: A Review
Lulu Ge, Keshab K. Parhi
Hyperdimensional (HD) computing is built upon its unique data type referred to as hypervectors. The dimension of these hypervectors is typically in the range of tens of thousands.…
A Gradient-Interleaved Scheduler for Energy-Efficient Backpropagation for Training Neural Networks
Nanda Unnikrishnan, Keshab K. Parhi
This paper addresses design of accelerators using systolic architectures for training of neural networks using a novel gradient interleaving approach. Training the neural network i…