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US 2022/0188609 A1Published application
Resource aware neural network model dynamic updating
AssigneePlantronics, Inc.
InventorsYong YAN, David A. BRYAN
Life of this patent
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AssigneePlantronics, Inc.
InventorsYong YAN, David A. BRYAN
Estimating the term…
Resources of an embedded system, such as RAM utilization and available processor cycles or bandwidth are monitored. Neural network models of varying size and computational load for given neural networks are utilized in conjunction with this resource monitoring. The neural network model used for a particular neural network is dynamically varied based on the resource monitoring. In one example, neural network models of varying precision are stored and the best model for the available RAM and processor cycles is loaded. In one example, neural network model weight values are quantized before being loaded for use, the level of quantization being based on the available RAM and processor cycles. This dynamic adaption of the neural network models allows other processes in the embedded system to operate normally and yet allows the neural network to operate at the maximum capability allowed for a given period.
A method of operating a device which includes operating neural networks, the device having a processor and RAM and executing a plurality of modules of varying functionality, including at least one neural network, the method comprising:
A device comprising:
A non-transitory processor readable memory containing programs that when executed cause a processor to perform the following method of operating a device which includes operating neural networks, the device having a processor and RAM and executing a plurality of modules of varying functionality, including at least one neural network, the method comprising:
Dependencies are inferred from the claim text.