Invention Grant
- Patent Title: Machine learning in heterogeneous processing systems
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Application No.: US16214918Application Date: 2018-12-10
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Publication No.: US11315035B2Publication Date: 2022-04-26
- Inventor: Thomas Parnell , Celestine Duenner , Charalampos Pozidis , Dimitrios Sarigiannis
- 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: Cantor Colburn LLP
- Agent Daniel Morris
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06K9/62 ; G06F17/11 ; G06N7/08 ; G06F7/58

Abstract:
Computer-implemented methods are provided for implementing training of a machine learning model in a heterogeneous processing system comprising a host computer operatively interconnected with an accelerator unit. The training includes a stochastic optimization process for optimizing a function of a training data matrix X, having data elements Xi,j with row coordinates i=1 to n and column coordinates j=1 to m, and a model vector w having elements wj. For successive batches of the training data, defined by respective subsets of one of the row coordinates and column coordinates, random numbers associated with respective coordinates in a current batch b are generated in the host computer and sent to the accelerator unit. In parallel with generating the random numbers for batch b, batch b is copied from the host computer to the accelerator unit.
Public/Granted literature
- US20200184369A1 MACHINE LEARNING IN HETEROGENEOUS PROCESSING SYSTEMS Public/Granted day:2020-06-11
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