Cloud computing data compression for allreduce in deep learning

In deep learning, and in particular, for data compression for allreduce in deep learning, a gradient may be compressed for synchronization in a data parallel deep neural network training for allreduce by sharing a consensus vector between each node in a plurality of nodes to ensure identical indexin...

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Hauptverfasser:	Finkler, Ulrich, Zhang, Wei, Cho, Minsik
Format:	Patent
Sprache:	eng
Schlagworte:	BASIC ELECTRONIC CIRCUITRY CALCULATING CODE CONVERSION IN GENERAL CODING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DECODING ELECTRICITY PHYSICS
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creator	Finkler, Ulrich Zhang, Wei Cho, Minsik
description	In deep learning, and in particular, for data compression for allreduce in deep learning, a gradient may be compressed for synchronization in a data parallel deep neural network training for allreduce by sharing a consensus vector between each node in a plurality of nodes to ensure identical indexing in each of the plurality of nodes prior to performing sparse encoding.
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title	Cloud computing data compression for allreduce in deep learning
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