ELECTRONIC DEVICE INCLUDING INTERPOSER

    公开(公告)号:US20210022247A1

    公开(公告)日:2021-01-21

    申请号:US16868941

    申请日:2020-05-07

    Abstract: An electronic device is provided. The electronic device includes a housing, a first printed circuit board disposed in an internal space of the housing and including first conductive terminals, and a second printed circuit board disposed parallel to the first printed circuit board in the internal space and including second conductive terminals electrically connected to the first conductive terminals. The second printed circuit board includes at least some conductive terminals of the second conductive terminals, or at least one connection failure prevention structure disposed around at least some conductive terminals of the second conductive terminals.

    ELECTRONIC DEVICE INCLUDING INTERPOSER

    公开(公告)号:US20220256705A1

    公开(公告)日:2022-08-11

    申请号:US17728363

    申请日:2022-04-25

    Abstract: An electronic device is provided that includes a first circuit board including a first electronic component and a second electronic component disposed on a side of the first circuit board, a second circuit board spaced apart from the first circuit board and having a side facing the side of the first circuit board on which the first electronic component and the second electronic component are disposed, a first interposer disposed between the first circuit board and the second circuit board to form an inner space between the first circuit board and the second circuit board, and a second interposer disposed between the first circuit board and the second circuit board to divide the inner space into a first region and a second region, and wherein the first interposer and the second interposer electrically connect the first circuit board to the second circuit board.

    METHOD, ACCELERATOR, AND ELECTRONIC DEVICE WITH TENSOR PROCESSING

    公开(公告)号:US20210406646A1

    公开(公告)日:2021-12-30

    申请号:US17091338

    申请日:2020-11-06

    Abstract: A processor-implemented tensor processing method includes: receiving a request to process a neural network including a normalization layer by an accelerator; and generating an instruction executable by the accelerator in response to the request, wherein, by executing the instruction, the accelerator is configured to determine an intermediate tensor corresponding to a result of a portion of operations of the normalization layer, by performing, in a channel axis direction, a convolution based on an input tensor and a kernel, wherein the input tensor is of the normalization layer and includes a plurality of channels, a number of input channels of the kernel is determined based on the input tensor, and scaling values of elements of the kernel are determined based on the number of input channels.

    CIRCUIT BOARD INCLUDING INSULATING LAYER HAVING A PLURALITY OF DIELECTRICS WITH DIFFERENT DIELECTRIC LOSS, AND ELECTRONIC DEVICE INCLUDING THE CIRCUIT BOARD

    公开(公告)号:US20200006853A1

    公开(公告)日:2020-01-02

    申请号:US16460937

    申请日:2019-07-02

    Abstract: An electronic device includes a communication circuit electrically connected with a circuit board. The circuit board includes a first portion comprising a first layered structure in which a wiring layer and a first insulating layer are alternately positioned, and a second portion comprising a second layered structure in which the wiring layer and the first insulating layer are alternately positioned and a second insulating layer. At least one antenna patch is positioned on or within the second insulating layer. A conductive line penetrates the second layered structure and the second insulating layer and electrically connects the at least one antenna patch and the communication circuit. The first insulating layer has a first loss tangent value, and the second insulating layer has a second loss tangent value smaller than the first loss tangent value.

    METHOD AND APPARATUS FOR GENERATING FIXED-POINT QUANTIZED NEURAL NETWORK

    公开(公告)号:US20190042948A1

    公开(公告)日:2019-02-07

    申请号:US16051788

    申请日:2018-08-01

    Abstract: A method of generating a fixed-point quantized neural network includes analyzing a statistical distribution for each channel of floating-point parameter values of feature maps and a kernel for each channel from data of a pre-trained floating-point neural network, determining a fixed-point expression of each of the parameters for each channel statistically covering a distribution range of the floating-point parameter values based on the statistical distribution for each channel, determining fractional lengths of a bias and a weight for each channel among the parameters of the fixed-point expression for each channel based on a result of performing a convolution operation, and generating a fixed-point quantized neural network in which the bias and the weight for each channel have the determined fractional lengths.

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