US 11,727,276 B2
Processing method and accelerating device
Zai Wang, Pudong New Area (CN); Xuda Zhou, Pudong New Area (CN); Zidong Du, Pudong New Area (CN); and Tianshi Chen, Pudong New Area (CN)
Assigned to SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTD, Shanghai (CN)
Filed by Shanghai Cambricon Information Technology Co., Ltd., Pudong New Area (CN)
Filed on Nov. 28, 2019, as Appl. No. 16/699,046.
Application 16/699,046 is a continuation of application No. 16/699,027, filed on Nov. 28, 2019.
Application 16/699,027 is a continuation in part of application No. PCT/CN2018/088033, filed on May 23, 2018.
Claims priority of application No. 201710678038.8 (CN), filed on Aug. 9, 2017.
Prior Publication US 2020/0097831 A1, Mar. 26, 2020
Int. Cl. G06N 3/082 (2023.01); G06F 1/3296 (2019.01); G06F 9/38 (2018.01); G06F 13/16 (2006.01); G06N 3/04 (2023.01); G06N 3/084 (2023.01); G06F 16/28 (2019.01); G06N 3/063 (2023.01); G06F 12/0875 (2016.01); G06N 3/044 (2023.01); G06N 3/048 (2023.01)
CPC G06N 3/082 (2013.01) [G06F 1/3296 (2013.01); G06F 9/3877 (2013.01); G06F 12/0875 (2013.01); G06F 13/16 (2013.01); G06F 16/285 (2019.01); G06N 3/04 (2013.01); G06N 3/044 (2023.01); G06N 3/048 (2023.01); G06N 3/063 (2013.01); G06N 3/084 (2013.01); G06F 2212/452 (2013.01); G06F 2213/0026 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A data quantization method, comprising:
grouping weights of a neural network;
performing a clustering operation on each group of weights by using a clustering algorithm, dividing a group of weights into m classes, computing a center weight for each class, and replacing all the weights in each class by the center weights, where m is a positive integer;
encoding the center weight to get a weight codebook and a weight dictionary,
wherein the grouping includes grouping into a group, an inter-layer-based grouping, and an intra-layer-based grouping, and the method further includes grouping convolutional layers into one group, grouping fully connected layers by the intra-layer-based grouping, and grouping LSTM layers by the inter-layer-based grouping.