Spiking Neural Streaming Binary Arithmetic

no code implementations • 23 Mar 2022 • James B. Aimone, Aaron J. Hill, William M. Severa, Craig M. Vineyard

Boolean functions and binary arithmetic operations are central to standard computing paradigms.

Neuromorphic scaling advantages for energy-efficient random walk computation

no code implementations • 27 Jul 2021 • J. Darby Smith, Aaron J. Hill, Leah E. Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas Parekh, William Severa, James B. Aimone

Computing stands to be radically improved by neuromorphic computing (NMC) approaches inspired by the brain's incredible efficiency and capabilities.

Solving a steady-state PDE using spiking networks and neuromorphic hardware

no code implementations • 21 May 2020 • J. Darby Smith, William Severa, Aaron J. Hill, Leah Reeder, Brian Franke, Richard B. Lehoucq, Ojas D. Parekh, James B. Aimone

The widely parallel, spiking neural networks of neuromorphic processors can enable computationally powerful formulations.

BIG-bench Machine Learning Position

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

no code implementations • 21 Mar 2017 • Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson, Craig M. Vineyard, Jonathon Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James B. Aimone

Information in neural networks is represented as weighted connections, or synapses, between neurons.

speech-recognition Speech Recognition