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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Bibliographische Detailangaben
Hauptverfasser: Finkler, Ulrich, Zhang, Wei, Cho, Minsik
Format: Patent
Sprache:eng
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Zusammenfassung: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.