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公开(公告)号:US20210303980A1
公开(公告)日:2021-09-30
申请号:US17108927
申请日:2020-12-01
Inventor: Sungju RYU , Jae-Joon KIM , Youngtaek OH
Abstract: A method of processing of a sparsity-aware neural processing unit includes receiving a plurality of input activations (IA); obtaining a weight having a non-zero value in each weight output channel; storing the weight and the IA in a memory, and obtaining an input channel index comprising a memory address location in which the weight and the IA are stored; and arranging the non-zero weight of each weight output channel according to a row size of an index matching unit (IMU) and matching the IA to the weight in the IMU comprising a buffer memory storing the input channel index.
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公开(公告)号:US20230362498A1
公开(公告)日:2023-11-09
申请号:US18353801
申请日:2023-07-17
Inventor: Hyungjun KIM , Yulhwa KIM , Sungju RYU , Jae-Joon KIM
CPC classification number: H04N23/84 , G06T7/97 , G06T2207/20084 , G06T2207/20221
Abstract: An electronic system may include: a camera to capture a current image; an image processor to generate current image data items; and a splitter circuit to generate first and second images having respective first and second image data items. The splitter circuit splits each current image data item into a first image data item with a first set of bits and a second image data item with a second set of bits distinct from the first set of bits. The first and second image data items correspond to two distinct precisions less than a precision of the current image data items. The electronic system may also include distinct binary neural network circuits to independently process the first and second images to generate first and second processed image data items; and a merger circuit to combine the processed image data items to recover output image data items for display.
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公开(公告)号:US20210027142A1
公开(公告)日:2021-01-28
申请号:US16933889
申请日:2020-07-20
Inventor: Hyungjun KIM , Yulhwa KIM , Sungju RYU , Jae-Joon KIM
Abstract: Disclosed is a method of operating a neural network system. The method includes splitting input feature data into first splitting data corresponding to a first digit bit and second splitting data corresponding to a second digit bit different from the first digit bit, propagating the first splitting data through a first binary neural network, propagating the second splitting data through a second binary neural network, and merging first result data by propagation of the first splitting data and second result data by propagating the second splitting data to generate output feature data.
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