64 citations · 256 across the 76 of their papers we have counts for
10 papers · 1 filter
BMPQ: Bit-Gradient Sensitivity Driven Mixed-Precision Quantization of DNNs from Scratch
Souvik Kundu, Shikai Wang, Qirui Sun +2
Large DNNs with mixed-precision quantization can achieve ultra-high compression while retaining high classification performance. However, because of the challenges in finding an ac…
Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?
Gourav Datta, Peter A. Beerel
Spiking neural networks (SNNs), that operate via binary spikes distributed over time, have emerged as a promising energy efficient ML paradigm for resource-constrained devices. How…
Pipeline Parallelism for Inference on Heterogeneous Edge Computing
Yang Hu, Connor Imes, Xuanang Zhao +4
Deep neural networks with large model sizes achieve state-of-the-art results for tasks in computer vision (CV) and natural language processing (NLP). However, these large-scale mod…
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise
Souvik Kundu, Massoud Pedram, Peter A. Beerel
Low-latency deep spiking neural networks (SNNs) have become a promising alternative to conventional artificial neural networks (ANNs) because of their potential for increased energ…
Fun-SAT: Functional Corruptibility-Guided SAT-Based Attack on Sequential Logic Encryption
Yinghua Hu, Yuke Zhang, Kaixin Yang +3
The SAT attack has shown to be efficient against most combinational logic encryption methods. It can be extended to attack sequential logic encryption techniques by leveraging circ…
A High Performance and Robust FIFO Synchronizer-Interface for Crossing Clock Domains in SFQ Logic
Gourav Datta, Shidie Lin, Peter A. Beerel
Digital single-flux quantum (SFQ) technology promises to meet the demands of ultra low power and high speed computing needed for future exascale supercomputing platforms. However,…