Invention Grant
- Patent Title: Parallelizing the training of convolutional neural networks
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Application No.: US14684186Application Date: 2015-04-10
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Publication No.: US10540587B2Publication Date: 2020-01-21
- Inventor: Alexander Krizhevsky
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a convolutional neural network (CNN). The system includes a plurality of workers, wherein each worker is configured to maintain a respective replica of each of the convolutional layers of the CNN and a respective disjoint partition of each of the fully-connected layers of the CNN, wherein each replica of a convolutional layer includes all of the nodes in the convolutional layer, and wherein each disjoint partition of a fully-connected layer includes a portion of the nodes of the fully-connected layer.
Public/Granted literature
- US20150294219A1 PARALLELIZING THE TRAINING OF CONVOLUTIONAL NEURAL NETWORKS Public/Granted day:2015-10-15
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