Neuromorphic accelerator multitasking

    公开(公告)号:US11366998B2

    公开(公告)日:2022-06-21

    申请号:US15937486

    申请日:2018-03-27

    Abstract: Systems and techniques for neuromorphic accelerator multitasking are described herein. A neuron address translation unit (NATU) may receive a spike message. Here, the spike message includes a physical neuron identifier (PNID) of a neuron causing the spike. The NATU may then translate the PNID into a network identifier (NID) and a local neuron identifier (LNID). The NATU locates synapse data based on the NID and communicates the synapse data and the LNID to an axon processor.

    Apparatus and method for a tensor permutation engine

    公开(公告)号:US10908906B2

    公开(公告)日:2021-02-02

    申请号:US16024530

    申请日:2018-06-29

    Inventor: Berkin Akin

    Abstract: An apparatus and method for a tensor permutation engine. The TPE may include a read address generation unit (AGU) to generate a plurality of read addresses for the plurality of tensor data elements in a first storage and a write AGU to generate a plurality of write addresses for the plurality of tensor data elements in the first storage. The TPE may include a shuffle register bank comprising a register to read tensor data elements from the plurality of read addresses generated by the read AGU, a first register bank to receive the tensor data elements, and a shift register to receive a lowest tensor data element from each bank in the first register bank, each tensor data element in the shift register to be written to a write address from the plurality of write addresses generated by the write AGU.

    SPIKING NEURAL NETWORK ACCELERATOR USING EXTERNAL MEMORY

    公开(公告)号:US20190042920A1

    公开(公告)日:2019-02-07

    申请号:US15853282

    申请日:2017-12-22

    Abstract: System configurations and techniques for implementation of a neural network in neuromorphic hardware with use of external memory resources are described herein. In an example, a system for processing spiking neural network operations includes: a plurality of neural processor clusters to maintain neurons of the neural network, with the clusters including circuitry to determine respective states of the neurons and internal memory to store the respective states of the neurons; and a plurality of axon processors to process synapse data of synapses in the neural network, with the processors including circuitry to retrieve synapse data of respective synapses from external memory, evaluate the synapse data based on a received spike message, and propagate another spike message to another neuron based on the synapse data. Further details for use and access of the external memory and processing configurations for such neural network operations are also disclosed.

    PROCEDURAL NEURAL NETWORK SYNAPTIC CONNECTION MODES

    公开(公告)号:US20190042915A1

    公开(公告)日:2019-02-07

    申请号:US15941621

    申请日:2018-03-30

    Abstract: Systems and techniques for procedural neural network synaptic connection modes are described herein. A synapse list header may be loaded based on a received spike indication. A spike target generator may then execute a generator function identified in the synapse list header to produce a spike message. Here, the generator function accepts a current synapse value as input to produce the spike message. The spike message may then be communicated a neuron.

    Apparatus and method for a tensor permutation engine

    公开(公告)号:US11681528B2

    公开(公告)日:2023-06-20

    申请号:US17131424

    申请日:2020-12-22

    Inventor: Berkin Akin

    Abstract: An apparatus and method for a tensor permutation engine. The TPE may include a read address generation unit (AGU) to generate a plurality of read addresses for the plurality of tensor data elements in a first storage and a write AGU to generate a plurality of write addresses for the plurality of tensor data elements in the first storage. The TPE may include a shuffle register bank comprising a register to read tensor data elements from the plurality of read addresses generated by the read AGU, a first register bank to receive the tensor data elements, and a shift register to receive a lowest tensor data element from each bank in the first register bank, each tensor data element in the shift register to be written to a write address from the plurality of write addresses generated by the write AGU.

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