Open AccessNeuromorphic scaling advantages for energy-efficient random walk computations
Author(s) -
J. Darby Smith,
Aaron Hill,
Leah Reeder,
Brian Claude Franke,
Richard B. Lehoucq,
Ojas Parekh,
William Severa,
James B. Aimone
Publication year - 2020
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - Uncategorized
Resource type - Reports
DOI - 10.2172/1671377
Subject(s) - neuromorphic engineering , computer science , random walk , cognitive computing , leverage (statistics) , computation , probabilistic logic , unconventional computing , theoretical computer science , stochastic computing , supercomputer , artificial intelligence , computational science , artificial neural network , parallel computing , distributed computing , algorithm , cognition , mathematics , statistics , neuroscience , biology
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