Communications device and method
    51.
    发明授权

    公开(公告)号:US10447412B2

    公开(公告)日:2019-10-15

    申请号:US15577487

    申请日:2016-04-15

    Applicant: ARM LIMITED

    Abstract: A device comprises a coupling configured to couple signals to and from a communications path including at least a part of a human or animal body; a data transmitter coupled to the coupling and configured to transmit, from time to time, a data signal of at least a predetermined temporal duration via the communications path; and a data receiver coupled to the coupling and configured to detect the presence of a signal on the communications path at sets of one or more successive detection instances disposed between successive transmissions of the data signal by the data transmitter, the data receiver being configured so that the successive detection instances of a set are temporally separated by no more than the predetermined temporal duration; the device being configured to initiate a processing operation in response to a detection by the data receiver of the presence of a signal on the communications path.

    SYSTOLIC CONVOLUTIONAL NEURAL NETWORK
    52.
    发明申请

    公开(公告)号:US20190311243A1

    公开(公告)日:2019-10-10

    申请号:US15945952

    申请日:2018-04-05

    Applicant: Arm Limited

    Abstract: A circuit and method are provided for performing convolutional neural network computations for a neural network. The circuit includes a transposing buffer configured to receive actuation feature vectors along a first dimension and to output feature component vectors along a second dimension, a weight buffer configured to store kernel weight vectors along a first dimension and further configured to output kernel component vectors along a second dimension, and a systolic array configured to receive the kernel weight vectors along a first dimension and to receive the feature component vectors along a second dimension. The systolic array includes an array of multiply and accumulate (MAC) processing cells. Each processing cell is associated with an output value. The actuation feature vectors may be shifted into the transposing buffer along the first dimension and output feature component vectors may shifted out of the transposing buffer along the second dimension, providing efficient dataflow.

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