Invention Grant
- Patent Title: Reducing power consumption in a neural network environment using data management
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Application No.: US15847785Application Date: 2017-12-19
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Publication No.: US10996739B2Publication Date: 2021-05-04
- Inventor: Amol Ashok Ambardekar , Chad Balling McBride , George Petre , Kent D. Cedola , Larry Marvin Wall
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Newport IP, LLC
- Agent Han Gim
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08 ; G06N3/063 ; G06F17/16 ; G06F1/32 ; G06F1/3234

Abstract:
Techniques to provide for improved (i.e., reduced) power consumption in an exemplary neural network (NN) and/or Deep Neural Network (DNN) environment using data management. Improved power consumption in the NN/DNN may be achieved by reducing a number of bit flips needed to process operands associated with one or more storages. Reducing the number bit flips associated with the NN/DNN may be achieved by multiplying an operand associated with a first storage with a plurality of individual operands associated with a plurality of kernels of the NN/DNN. The operand associated with the first storage may be neuron input data and the plurality of individual operands associated with the second storage may be weight values for multiplication with the neuron input data. The plurality of kernels may be arranged or sorted and subsequently processed in a manner that improves power consumption in the NN/DNN.
Public/Granted literature
- US20190187771A1 REDUCING POWER CONSUMPTION IN A NEURAL NETWORK ENVIRONMENT USING DATA MANAGEMENT Public/Granted day:2019-06-20
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