Training a neural network using a non-homogenous set of reconfigurable processors

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United States of America

PATENT NO 11893424
SERIAL NO

17582925

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Abstract

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A system for training parameters of a neural network includes a processing node with a processor reconfigurable at a first level of configuration granularity and a controller reconfigurable at a finer level of configuration granularity. The processor is configured to execute a first dataflow segment of the neural network with training data to generate a predicted output value using a set of neural network parameters, calculate a first intermediate result for a parameter based on the predicted output value, a target output value, and a parameter gradient, and provide the first intermediate result to the controller. The controller is configured to receive a second intermediate result over a network, and execute a second dataflow segment, dependent upon the first intermediate result and the second intermediate result, to generate a third intermediate result indicative of an update of the parameter.

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Patent Owner(s)

  • SAMBANOVA SYSTEMS, INC.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Grohoski, Gregory Frederick Bee Cave, US 34 152
Jairath, Sumti Santa Clara, US 67 295
Kumar, Ravinder Fremont, US 40 212
Leung, Kin Hing Cupertino, US 25 41
Raumann, Martin Russell San Leandro, US 6 11
Shah, Bandish B San Francisco, US 6 11
Zheng, Qi Fremont, US 82 483

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