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Patent Searching and Data


Title:
DEEP LEARNING ACCELERATION HARDWARE DEVICE
Document Type and Number:
WIPO Patent Application WO/2020/153513
Kind Code:
A1
Abstract:
Provided is a deep learning acceleration hardware device. An acceleration hardware device according to an embodiment of the present invention comprises: a cache for receiving, from an external memory, inputs of IFmap and Weight of multi-channels; a plurality of line memories for storing the IFmap and the Weight that are input to the cache while distinguishing therebetween; and WDMAs for respectively processing and storing the IFmap and the Weight that are separately stored in the line memories. Accordingly, it is possible to reduce the number of accesses to a large-capacity external memory in order for a deep learning accelerator to process data per same channel/Weight each time, increase data re-usability, and simultaneously improve a processing speed through minimization of data buffering time of the accelerator by reducing a peak bandwidth and appropriately distributing a bandwidth.

Inventors:
LEE SANG SEOL (KR)
JANG SUNG JOON (KR)
Application Number:
PCT/KR2019/000968
Publication Date:
July 30, 2020
Filing Date:
January 23, 2019
Export Citation:
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Assignee:
KOREA ELECTRONICS TECHNOLOGY (KR)
International Classes:
G06N3/063; G06F15/78; G06T1/00
Foreign References:
KR20180136720A2018-12-26
KR20180060149A2018-06-07
KR20180075913A2018-07-05
KR101687081B12016-12-28
Other References:
SZE, VIVIENNE ET AL.: "Efficient Processing of Deep Neural Networks: A tutorial and Survey", ARXIV: 1703.09039V2, 13 August 2017 (2017-08-13), XP080759895, Retrieved from the Internet [retrieved on 20190930]
Attorney, Agent or Firm:
NAM, Choong Woo (KR)
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