Training of artificial neural networks

Methods and apparatus are provided for training an artificial neural network, having a succession of neuron layers with interposed synaptic layers each storing a respective set of weights {w} for weighting signals propagated between its adjacent neuron layers, via an iterative cycle of signal propag...

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Main Authors Le Gallo-Bourdeau, Manuel, Piveteau, Christophe, Boybat Kara, Irem, Sasidharan Rajalekshmi, Nandakumar, Eleftheriou, Evangelos Stavros, Sebastian, Abu
Format Patent
LanguageEnglish
Published 12.07.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
INFORMATION STORAGE
PHYSICS
STATIC STORES
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Summary:Methods and apparatus are provided for training an artificial neural network, having a succession of neuron layers with interposed synaptic layers each storing a respective set of weights {w} for weighting signals propagated between its adjacent neuron layers, via an iterative cycle of signal propagation and weight-update calculation operations. Such a method includes, for at least one of the synaptic layers, providing a plurality Pl of arrays of memristive devices, each array storing the set of weights of that synaptic layer Sl in respective memristive devices, and, in a signal propagation operation, supplying respective subsets of the signals to be weighted by the synaptic layer Sl in parallel to the Pl arrays. The method also includes, in a weight-update calculation operation, calculating updates to respective weights stored in each of the Pl arrays in dependence on signals propagated by the neuron layers.
Bibliography:Application Number: US201916352922