Invention Grant
- Patent Title: Cloud computing data compression for allreduce in deep learning
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Application No.: US16367244Application Date: 2019-03-28
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Publication No.: US11501160B2Publication Date: 2022-11-15
- Inventor: Minsik Cho , Wei Zhang , Ulrich Finkler
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Griffiths & Seaton PLLC
- Main IPC: G06N3/08
- IPC: G06N3/08 ; H03M7/30 ; G06N3/04

Abstract:
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.
Public/Granted literature
- US20200311539A1 CLOUD COMPUTING DATA COMPRESSION FOR ALLREDUCE IN DEEP LEARNING Public/Granted day:2020-10-01
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