- Patent Title: Data parallelism and halo exchange for distributed machine learning
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Application No.: US15869551Application Date: 2018-01-12
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Publication No.: US11373266B2Publication Date: 2022-06-28
- Inventor: Dipankar Das , Karthikeyan Vaidyanathan , Srinivas Sridharan
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Jaffery Watson Mendonsa & Hamilton LLP
- Main IPC: G06T1/20
- IPC: G06T1/20 ; G06T1/60 ; G06N3/08 ; G06N3/063 ; G06N3/04

Abstract:
One embodiment provides for a method of transmitting data between multiple compute nodes of a distributed compute system, the method comprising multi-dimensionally partitioning data of a feature map across multiple nodes for distributed training of a convolutional neural network; performing a parallel convolution operation on the multiple partitions to train weight data of the neural network; and exchanging data between nodes to enable computation of halo regions, the halo regions having dependencies on data processed by a different node.
Public/Granted literature
- US20180322606A1 DATA PARALLELISM AND HALO EXCHANGE FOR DISTRIBUTED MACHINE LEARNING Public/Granted day:2018-11-08
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