363 citations · 455 across the 10 of their papers we have counts for
7 papers · 1 filter
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing
Prasanna Date, Chathika Gunaratne, Shruti Kulkarni +3
In many neuromorphic workflows, simulators play a vital role for important tasks such as training spiking neural networks (SNNs), running neuroscience simulations, and designing, i…
Encoding Integers and Rationals on Neuromorphic Computers using Virtual Neuron
Prasanna Date, Shruti Kulkarni, Aaron Young +3
Neuromorphic computers perform computations by emulating the human brain, and use extremely low power. They are expected to be indispensable for energy-efficient computing in the f…
Neuromorphic Computing is Turing-Complete
Prasanna Date, Catherine Schuman, Bill Kay +1
Neuromorphic computing is a non-von Neumann computing paradigm that performs computation by emulating the human brain. Neuromorphic systems are extremely energy-efficient and known…
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment
Maryam Parsa, Catherine D. Schuman, Prasanna Date +8
Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms…
Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks
Mihaela Dimovska, Travis Johnston, Catherine D. Schuman +2
Inspired by the connectivity mechanisms in the brain, neuromorphic computing architectures model Spiking Neural Networks (SNNs) in silicon. As such, neuromorphic architectures are…
A Survey of Neuromorphic Computing and Neural Networks in Hardware
Catherine D. Schuman, Thomas E. Potok, Robert M. Patton +4
Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture. This biologica…