US 11,657,324 B2
Method, electronic device, and computer program product for processing data
Jin Li, Shanghai (CN); Jinpeng Liu, Shanghai (CN); and WuiChak Wong, Xiamen (CN)
Assigned to EMC IP Holding Company LLC, Hopkinton, MA (US)
Filed by EMC IP Holding Company LLC, Hopkinton, MA (US)
Filed on May 28, 2020, as Appl. No. 16/886,131.
Claims priority of application No. 202010367906.2 (CN), filed on Apr. 30, 2020.
Prior Publication US 2021/0342741 A1, Nov. 4, 2021
Int. Cl. G06F 17/00 (2019.01); G06T 1/00 (2006.01); G06N 20/00 (2019.01); G06T 1/20 (2006.01); G06F 17/16 (2006.01)
CPC G06N 20/00 (2019.01) [G06F 17/16 (2013.01); G06T 1/20 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for processing data, comprising:
determining a factor associated with a first input of a deep learning model, wherein the factor affects the number of threads for executing the deep learning model;
generating a plurality of first partial inputs by using the first input based on the factor, wherein each first partial input in the plurality of first partial inputs is a part of the first input; and
performing an operation on the plurality of first partial inputs by using the deep learning model, and generating an output of the deep learning model;
wherein the operation is performed in parallel on select ones of the first partial inputs of the plurality of first partial inputs;
wherein the factor determined is at least one of a channel number and a size;
wherein when the factor is the size, the operation performed by the deep learning model is a cross-multiplication operation, the deep learning model further has a second input, and the first input is divided into the plurality of first partial inputs based on determined relative sizes of the first input and the second input; and
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.