PARTIAL ACTIVATION OF MULTIPLE PATHWAYS IN NEURAL NETWORKS

    公开(公告)号:US20250061306A1

    公开(公告)日:2025-02-20

    申请号:US18931819

    申请日:2024-10-30

    Inventor: Eli DAVID Eri RUBIN

    Abstract: A device, system, and method for approximating a neural network comprising N synapses or filters. The neural network may be partially-activated by iteratively executing a plurality of M partial pathways of the neural network to generate M partial outputs, wherein the M partial pathways respectively comprise M different continuous sequences of synapses or filters linking an input layer to an output layer. The M partial pathways may cumulatively span only a subset of the N synapses or filters such that a significant number of the remaining the N synapses or filters are not computed. The M partial outputs of the M partial pathways may be aggregated to generate an aggregated output approximating an output generated by fully-activating the neural network by executing a single instance of all N synapses or filters of the neural network. Training or prediction of the neural network may be performed based on the aggregated output.

    ACTIVE TRANSISTOR RANDOM NUMBER GENERATOR (RNG) CIRCUIT WITH MEMS ENTROPY

    公开(公告)号:US20250045021A1

    公开(公告)日:2025-02-06

    申请号:US18661437

    申请日:2024-05-10

    Inventor: James L. Tucker

    Abstract: Systems and methods for an active transistor RNG circuit with MEMS entropy are described herein. In one example, an RNG circuit includes one or more MEMS structures configured to provide an output, wherein the output includes active oscillations, charge, resistance, capacitance, and/or inductance values. The RNG circuit further includes active transistor RNG circuitry communicatively coupled to the one or more MEMS structures. The active transistor RNG circuitry is configured to generate a random number output based on the output by the one or more MEMS structures. The random number output generated by the active transistor RNG circuitry is an output of the RNG circuit.

    Storage device and data access method

    公开(公告)号:US12197629B2

    公开(公告)日:2025-01-14

    申请号:US17574670

    申请日:2022-01-13

    Abstract: A storage device and a data access method are provided. The storage device includes a primary storage unit and at least one additional unit. The primary storage unit includes: a primary memory element configured to store secret data and a primary access unit configured to receive an external access command. Each additional unit is configured to receive the external access command. Each additional unit includes: an additional memory element configured to store non-specific data, a local access generation element configured to trigger generating an internal access command based on the external access command, and an additional access unit configured to receive a local access command. The primary storage unit and each additional unit are coupled to a same power rail and a connection wire to simultaneously receive the external access command to parallelly (simultaneously) access the secret data and the non-specific data stored in each additional unit.

    Method and apparatus for neural network quantization

    公开(公告)号:US12190231B2

    公开(公告)日:2025-01-07

    申请号:US15697035

    申请日:2017-09-06

    Abstract: Apparatuses and methods of manufacturing same, systems, and methods for performing network parameter quantization in deep neural networks are described. In one aspect, multi-dimensional vectors representing network parameters are constructed from a trained neural network model. The multi-dimensional vectors are quantized to obtain shared quantized vectors as cluster centers, which are fine-tuned. The fine-tuned and shared quantized vectors/cluster centers are then encoded. Decoding reverses the process.

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