Methods and apparatus for emulating power loss event on an integrated circuit

    公开(公告)号:US10747923B2

    公开(公告)日:2020-08-18

    申请号:US16365032

    申请日:2019-03-26

    Inventor: Jing Zhang Yan Li

    Abstract: Programmable integrated circuits may be used to perform hardware emulation of an application-specific integrated circuit (ASIC) design. The ASIC design may be loaded onto the programmable integrated circuit as a circuit under test (CUT). During hardware emulation operations, an emulation host may be used to coordinate testing of the CUT on the programmable device. To help emulate a power gating event for the ASIC design, the programmable device may be provided with an encoder at the input of the CUT, a decoder at the output of the CUT, and a pseudorandom number generator (PRNG) that outputs a value for adjusting the encoder and decoder. The value output from the PRNG stays fixed when there is no power loss, but will change to a new value during a power gating event. Operated in this way, the data read out from the CUT after the power gating event is effectively corrupted.

    DYNAMIC NEURAL NETWORK SURGERY
    3.
    发明申请

    公开(公告)号:US20250045582A1

    公开(公告)日:2025-02-06

    申请号:US18804720

    申请日:2024-08-14

    Abstract: Techniques related to compressing a pre-trained dense deep neural network to a sparsely connected deep neural network for efficient implementation are discussed. Such techniques may include iteratively pruning and splicing available connections between adjacent layers of the deep neural network and updating weights corresponding to both currently disconnected and currently connected connections between the adjacent layers.

    DYNAMIC NEURAL NETWORK SURGERY
    8.
    发明申请

    公开(公告)号:US20190188567A1

    公开(公告)日:2019-06-20

    申请号:US16328689

    申请日:2016-09-30

    CPC classification number: G06N3/08 G06N3/04 G06N3/0454 G06N3/082

    Abstract: Techniques related to compressing a pre-trained dense deep neural network to a sparsely connected deep neural network for efficient implementation are discussed. Such techniques may include iteratively pruning and splicing available connections between adjacent layers of the deep neural network and updating weights corresponding to both currently disconnected and currently connected connections between the adjacent layers.

    METHODS AND APPARATUS FOR EMULATING POWER LOSS EVENT ON AN INTEGRATED CIRCUIT

    公开(公告)号:US20190220559A1

    公开(公告)日:2019-07-18

    申请号:US16365032

    申请日:2019-03-26

    Inventor: Jing Zhang Yan Li

    Abstract: Programmable integrated circuits may be used to perform hardware emulation of an application-specific integrated circuit (ASIC) design. The ASIC design may be loaded onto the programmable integrated circuit as a circuit under test (CUT). During hardware emulation operations, an emulation host may be used to coordinate testing of the CUT on the programmable device. To help emulate a power gating event for the ASIC design, the programmable device may be provided with an encoder at the input of the CUT, a decoder at the output of the CUT, and a pseudorandom number generator (PRNG) that outputs a value for adjusting the encoder and decoder. The value output from the PRNG stays fixed when there is no power loss, but will change to a new value during a power gating event. Operated in this way, the data read out from the CUT after the power gating event is effectively corrupted.

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