99 citations · 330 across the 21 of their papers we have counts for
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A Deep Dive into the Computational Fidelity of High Variability Low Energy Barrier Magnet Technology for Accelerating Optimization and Bayesian Problems
Md Golam Morshed, Samiran Ganguly, Avik W. Ghosh
Low energy barrier magnet (LBM) technology has recently been proposed as a candidate for accelerating algorithms based on energy minimization and probabilistic graphs because their…
Choose your tools carefully: A Comparative Evaluation of Deterministic vs. Stochastic and Binary vs. Analog Neuron models for Implementing Emerging Computing Paradigms
Md Golam Morshed, Samiran Ganguly, Avik W. Ghosh
Neuromorphic computing, commonly understood as a computing approach built upon neurons, synapses, and their dynamics, as opposed to Boolean gates, is gaining large mindshare due to…
Roadmap for Unconventional Computing with Nanotechnology
Giovanni Finocchio, Jean Anne C. Incorvia, Joseph S. Friedman +48
In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same ti…
Building Reservoir Computing Hardware Using Low Energy-Barrier Magnetics
Samiran Ganguly, Avik W. Ghosh
Biologically inspired recurrent neural networks, such as reservoir computers are of interest in designing spatio-temporal data processors from a hardware point of view due to the s…
Analog Signal Processing Using Stochastic Magnets
Samiran Ganguly, Kerem Y. Camsari, Avik W. Ghosh
We present a low barrier magnet based compact hardware unit for analog stochastic neurons and demonstrate its use as a building-block for neuromorphic hardware. By coupling circula…
Reservoir Computing using Stochastic p-Bits
Samiran Ganguly, Kerem Y. Camsari, Avik W. Ghosh
We present a general hardware framework for building networks that directly implement Reservoir Computing, a popular software method for implementing and training Recurrent Neural…