CNN SEAMLESS TILE PROCESSING FOR LOW-POWER INFERENCE ACCELERATOR

    公开(公告)号:US20240112297A1

    公开(公告)日:2024-04-04

    申请号:US17957689

    申请日:2022-09-30

    CPC classification number: G06T1/60

    Abstract: Methods and devices are provided for processing image data on a sub-frame portion basis using layers of a convolutional neural network. The processing device comprises memory and a processor. The processor is configured to determine, for an input tile of an image, a receptive field via backward propagation and determine a size of the input tile based on the receptive field and an amount of local memory allocated to store data for the input tile. The processor determines whether the amount of local memory allocated to store the data of the input tile and padded data for the receptive field.

    Quality-of-Service Partition Configuration
    3.
    发明公开

    公开(公告)号:US20240111596A1

    公开(公告)日:2024-04-04

    申请号:US17955613

    申请日:2022-09-29

    CPC classification number: G06F9/505 G06F9/542

    Abstract: A scheduler of an apparatus exposes an application programming interface (API) usable to specify quality-of-service (QoS) parameters, e.g., latency, throughput, and so forth. An application, for instance, specifies the QoS parameters for a workload to be processed using a hardware compute unit. The QoS parameters are employed by the scheduler as a basis to configure a partition within a hardware compute unit. The partition is configured such that processing resources that are available via the partition to process the workload comply with the specified quality-of-service.

    Selecting a Tiling Scheme for Processing Instances of Input Data Through a Neural Netwok

    公开(公告)号:US20240111840A1

    公开(公告)日:2024-04-04

    申请号:US17957508

    申请日:2022-09-30

    CPC classification number: G06K9/6227 G06K9/6261 G06N3/04

    Abstract: An electronic device uses a tiling scheme selected from among a set of tiling schemes for processing instances of input data through a neural network. Each of the tiling schemes is associated with a different arrangement of portions into which instances of input data are divided for processing in the neural network. In operation, processing circuitry in the electronic device acquires information about a neural network and properties of the processing circuitry. The processing circuitry then selects a given tiling scheme from among a set of tiling schemes based on the information. The processing circuitry next processes instances of input data in the neural network using the given tiling scheme. Processing each instance of input data in the neural network includes dividing the instance of input data into portions based on the given tiling scheme, separately processing each of the portions in the neural network, and combining the respective outputs to generate an output for the instance of input data.

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