Dynamic design method to improve the adaptability of acceleration units to neural networks

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United States of America

PATENT NO 12260320
APP PUB NO 20220284272A1
SERIAL NO

17363141

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Abstract

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A method is disclosed to dynamically design acceleration units of neural networks. The method comprises steps of generating plural circuit description files through a neural network model; reading a model weight of the neural network model to determine a model data format of the neural network model; selecting one circuit description file from the plural circuit description files according to the model data format, so that the chip is reconfigured according to the selected circuit description file to form an acceleration unit adapted to the model data format. The acceleration unit is suitable for running a data segmentation algorithm, which may accelerate the inference process of the neural network model. Through this method the chip may be dynamically reconfigured into an efficient acceleration unit for the different model data format, thereby speeding up the inference process of the neural network model.

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Patent OwnerAddress
NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY#43 SEC 4 KEELUNG RD TAIPEI 10607

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Chang, Meng-Wei Taipei, TW 1 0
Su, Shun-Feng Taipei, TW 2 2

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