DATA FIXED-POINT METHOD AND DEVICE
    1.
    发明申请

    公开(公告)号:US20200234133A1

    公开(公告)日:2020-07-23

    申请号:US16842145

    申请日:2020-04-07

    Abstract: A data fixed-point method, includes: calculating a maximum output value in a first target layer of a neural network for each input sample of a plurality of input samples; selecting at least two of a plurality of maximum output values as fixed-point reference values; determining a reference integer part bit width according to each of the fixed-point reference values; and performing an accuracy test based on a preset output value total bit width and each reference integer part bit width, to determine a reference integer part bit width with a highest accuracy as an integer part bit width used by the first target layer when output values are fixed-pointed.

    METHOD, APPARATUS, ACCELERATOR, SYSTEM AND MOVABLE DEVICE FOR PROCESSING NEURAL NETWORK

    公开(公告)号:US20200285942A1

    公开(公告)日:2020-09-10

    申请号:US16884729

    申请日:2020-05-27

    Abstract: A method for processing across neural networks includes: when processing a last block of a plurality of blocks of an i-th layer of a first neural network, reading data of a first block of a plurality of blocks of a k-th layer of a second neural network from a memory; and processing the first block of the plurality of blocks of the k-th layer of the second neural network according to the data of the first block of the plurality of blocks of the k-th layer of the second neural network after processing the last block of the plurality of blocks of the i-th layer of the first neural network. 1≤i≤N, N is a number of layers of the first neural network; and 1≤k≤M, M is a number of layers of the second neural network.

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