Structural descriptions for neurosynaptic networks

    公开(公告)号:US11151444B2

    公开(公告)日:2021-10-19

    申请号:US15908403

    申请日:2018-02-28

    摘要: Embodiments of the invention provide a method comprising creating a structural description for at least one neurosynaptic core circuit. Each core circuit comprises an interconnect network including plural electronic synapses for interconnecting one or more electronic neurons with one or more electronic axons. The structural description defines a desired neuronal activity for the core circuits. The desired neuronal activity is simulated by programming the core circuits with the structural description. The structural description controls routing of neuronal firing events for the core circuits.

    LEARNED STEP SIZE QUANTIZATION
    4.
    发明申请

    公开(公告)号:US20210264279A1

    公开(公告)日:2021-08-26

    申请号:US16796397

    申请日:2020-02-20

    IPC分类号: G06N3/08 G06F17/16 G06N3/04

    摘要: Learned step size quantization in artificial neural network is provided. In various embodiments, a system comprises an artificial neural network and a computing node. The artificial neural network comprises: a quantizer having a configurable step size, the quantizer adapted to receive a plurality of input values and quantize the plurality of input values according to the configurable step size to produce a plurality of quantized input values, at least one matrix multiplier configured to receive the plurality of quantized input values from the quantizer and to apply a plurality of weights to the quantized input values to determine a plurality of output values having a first precision, and a multiplier configured to scale the output values to a second precision. The computing node is operatively coupled to the artificial neural network and is configured to: provide training input data to the artificial neural network, and optimize the configurable step size based on a gradient through the quantizer and the training input data.

    Transform for a neurosynaptic core circuit

    公开(公告)号:US10832121B2

    公开(公告)日:2020-11-10

    申请号:US16391092

    申请日:2019-04-22

    摘要: Embodiments of the present invention provide a method for feature extraction comprising generating synaptic connectivity information for a neurosynaptic core circuit. The core circuit comprises one or more electronic neurons, one or more electronic axons, and an interconnect fabric including a plurality of synapse devices for interconnecting the neurons with the axons. The method further comprises initializing the interconnect fabric based on the synaptic connectivity information generated, and extracting a set of features from input received via the electronic axons. The set of features extracted comprises a set of features with reduced correlation.

    MULTI-COMPARTMENT NEURONS WITH NEURAL CORES
    10.
    发明申请

    公开(公告)号:US20200034687A1

    公开(公告)日:2020-01-30

    申请号:US16592650

    申请日:2019-10-03

    摘要: Embodiments of the invention provide a neural core circuit comprising a synaptic interconnect network including plural electronic synapses for interconnecting one or more source electronic neurons with one or more target electronic neurons. The interconnect network further includes multiple axon paths and multiple dendrite paths. Each synapse is at a cross-point junction of the interconnect network between a dendrite path and an axon path. The core circuit further comprises a routing module maintaining routing information. The routing module routes output from a source electronic neuron to one or more selected axon paths. Each synapse provides a configurable level of signal conduction from an axon path of a source electronic neuron to a dendrite path of a target electronic neuron.