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Title:
DEPLOYING PARALLELIZABLE DEEP LEARNING MODELS BY ADAPTING TO THE COMPUTING DEVICES
Document Type and Number:
WIPO Patent Application WO/2022/227798
Kind Code:
A1
Abstract:
In an approach to deploying parallelizable deep learning models by adapting to the computing devices, a deep learning model is split into a plurality of slices, where each slice can exchange data with related slices. Virtual models are created from the plurality of slices, where the virtual models are based on capabilities of a plurality of devices on which the one or more virtual models are to be deployed, and further where each virtual model contains each slice of the plurality of slices. The one or more virtual models are stored in a cache. Responsive to determining that the deep learning model is to be deployed on one or more devices, a candidate model is selected from the virtual models in the cache, where the selection is based on information from a device monitor about the devices.

Inventors:
YIN KUNYAN (CN)
YU CHAO (CN)
CHEN MINGJIN (CN)
SUN TENG (CN)
LI XIAOYE (CN)
Application Number:
PCT/CN2022/076419
Publication Date:
November 03, 2022
Filing Date:
February 16, 2022
Export Citation:
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Assignee:
IBM (US)
IBM CHINA CO LTD (CN)
International Classes:
G06K9/00
Foreign References:
CN108804974A2018-11-13
US20100246662A12010-09-30
Other References:
DEAN JEFFREY, GREG CORRADO, RAJAT MONGA, KAI CHEN, MATTHIEU DEVIN, MARK MAO, MARC'AURELIO RANZATO, ANDREW SENIOR, PAUL TUCKER, KE : "Large Scale Distributed Deep Networks", ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 25 (NIPS 2012), 3 December 2012 (2012-12-03), pages 1 - 9, XP055980970
JUYONG KIM, YOOKOON PARK, GUNHEE KIM, AND SUNG JU HWANG: "SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization", PROCEEDINGS OF THE 34TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING, 1 January 2017 (2017-01-01), pages 1 - 9, XP055534564
ZHIHAO JIA; MATEI ZAHARIA; ALEX AIKEN: "Beyond Data and Model Parallelism for Deep Neural Networks", ARXIV.ORG, 14 July 2018 (2018-07-14), pages 1 - 15, XP081117055
Attorney, Agent or Firm:
CCPIT PATENT AND TRADEMARK LAW OFFICE (CN)
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