149 citations · 591 across the 39 of their papers we have counts for
7 papers · 1 filter
Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices
Foroozan Karimzadeh, Ningyuan Cao, Brian Crafton +2
Deep neural networks (DNNs) have been emerged as the state-of-the-art algorithms in broad range of applications. To reduce the memory foot-print of DNNs, in particular for embedded…
Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer Learning
Aqeel Anwar, Arijit Raychowdhury
Smart and agile drones are fast becoming ubiquitous at the edge of the cloud. The usage of these drones are constrained by their limited power and compute capability. In this paper…
Design space exploration of Ferroelectric FET based Processing-in-Memory DNN Accelerator
Insik Yoon, Matthew Jerry, Suman Datta +1
In this letter, we quantify the impact of device limitations on the classification accuracy of an artificial neural network, where the synaptic weights are implemented in a Ferroel…
SCNIFFER: Low-Cost, Automated, Efficient Electromagnetic Side-Channel Sniffing
Josef Danial, Debayan Das, Santosh Ghosh +2
Electromagnetic (EM) side-channel analysis (SCA) is a prominent tool to break mathematically-secure cryptographic engines, especially on resource-constrained IoT devices. Presently…
Practical Approaches Towards Deep-Learning Based Cross-Device Power Side Channel Attack
Anupam Golder, Debayan Das, Josef Danial +3
Power side-channel analysis (SCA) has been of immense interest to most embedded designers to evaluate the physical security of the system. This work presents profiling-based cross-…
Direct Feedback Alignment with Sparse Connections for Local Learning
Brian Crafton, Abhinav Parihar, Evan Gebhardt +1
Recent advances in deep neural networks (DNNs) owe their success to training algorithms that use backpropagation and gradient-descent. Backpropagation, while highly effective on vo…