64 citations · 256 across the 76 of their papers we have counts for
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A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs
Souvik Kundu, Mahdi Nazemi, Peter A. Beerel +1
This paper presents a dynamic network rewiring (DNR) method to generate pruned deep neural network (DNN) models that are robust against adversarial attacks yet maintain high accura…
Modeling and Characterization of Metastability in Single Flux Quantum (SFQ) Synchronizers
Gourav Datta, Peter A. Beerel
Despite the promises of low-power and high-frequency of single-flux quantum (SFQ) technology, scaling these circuits remains a serious challenge that motivates the support of multi…
Formal Verification of Flow Equivalence in Desynchronized Designs
Jennifer Paykin, Brian Huffman, Daniel M. Zimmerman +1
Seminal work by Cortadella, Kondratyev, Lavagno, and Sotiriou includes a hand-written proof that a particular handshaking protocol preserves flow equivalence, a notion of equivalen…
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning
Sourya Dey, Saikrishna C. Kanala, Keith M. Chugg +1
We present Deep-n-Cheap -- an open-source AutoML framework to search for deep learning models. This search includes both architecture and training hyperparameters, and supports con…
Pre-defined Sparsity for Low-Complexity Convolutional Neural Networks
Souvik Kundu, Mahdi Nazemi, Massoud Pedram +2
The high energy cost of processing deep convolutional neural networks impedes their ubiquitous deployment in energy-constrained platforms such as embedded systems and IoT devices.…
qBSA: Logic Design of a 32-bit Block-Skewed RSFQ Arithmetic Logic Unit
Souvik Kundu, Gourav datta, Peter A. Beerel +1
Single flux quantum (SFQ) circuits are an attractive beyond-CMOS technology because they promise two orders of magnitude lower power at clock frequencies exceeding 25 GHz.However,…