Invention Grant
- Patent Title: Optimizing data partitioning and replacement strategy for convolutional neural networks
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Application No.: US16428748Application Date: 2019-05-31
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Publication No.: US11010308B2Publication Date: 2021-05-18
- Inventor: Jaewon Kim , Thi Huong Giang Nguyen
- Applicant: LG ELECTRONICS INC.
- Applicant Address: KR Seoul
- Assignee: LG ELECTRONICS INC.
- Current Assignee: LG ELECTRONICS INC.
- Current Assignee Address: KR Seoul
- Agency: Lee, Hong, Degerman, Kang & Waimey PC
- Main IPC: G06F12/126
- IPC: G06F12/126 ; G06N20/10 ; G06N3/063

Abstract:
Embodiments of the present disclosure include method for optimizing an internal memory for calculation of a convolutional layer of a convolutional neural network (CNN), the method including determining a computation cost of calculating the convolutional layer using each combination of a memory management scheme of a plurality of memory management schemes and data partition sizes of input feature map (IFM) data, kernel data, and output feature map (OFM) data to be loaded in the internal memory; identifying one combination of a memory management scheme and data partition sizes having a lowest computation cost for the convolutional layer; and implementing the CNN to use the one combination for calculation of the convolutional layer.
Public/Granted literature
- US20200050555A1 OPTIMIZING DATA PARTITIONING AND REPLACEMENT STRATEGY FOR CONVOLUTIONAL NEURAL NETWORKS Public/Granted day:2020-02-13
Information query
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