Reward-Based Updating of Synaptic Weights with A Spiking Neural Network to Perform Thermal Management

    公开(公告)号:US20190042916A1

    公开(公告)日:2019-02-07

    申请号:US16147573

    申请日:2018-09-28

    Abstract: Thermal management of a computing device is achieved using reward-based updating of synaptic weights of a spiking neural network. The thermal management is achieved using machine readable mediums having instructions that cause a processor to, during a first time window, generate weights to be applied to input trains of spikes from input neurons of a spiking neural network. The instructions further cause the processor to, based on a number of spikes included in an output train of spikes output by an output neuron of the spiking neural network during the first time window, adjust the workload of the processor, and, based on whether a surface temperature of an enclosure housing the processor meets a first threshold or a workload of the processor meets a second threshold, generate a penalty. The instructions also cause the processor to train the spiking neural network by updating the weights.

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