Techniques for efficiently operating a processing system based on energy characteristics of instructions and machine learning

A processing system comprising:

• a plurality of processors;
• and
• power management circuitry configured to:
• compare power being used by the plurality of processors and predicted power that is estimated to be used by the plurality of processors in the future;
• generate one or more control signals to change operating power of the plurality of processors in response to the comparison;
• and
• perform reinforcement learning to adapt the generation of the one or more control signals.

A method for dynamically controlling voltage and frequency settings for a plurality of processors configured to receive and execute instructions, the method comprising:

• measuring power currently used by the processors;
• predicting power of the processors by examining instructions to be executed by the processors;
• determine an error between the current power and the predicted power;
• generate one or more signals to change operating frequency and/or voltage to reduce the error;
• and
• perform reinforcement learning to adapt the generating of the one or more signals.

A controller comprising:

• a power monitor configured to monitor a voltage and/or current being supplied to a plurality of processors;
• circuitry configured to receive, from the plurality of processors, signals representing estimated energy consumption for executing instructions in the future, and to predict, based on aggregation of the received signals, power that will be used by the processors in the future for executing said instructions;
• and
• a self-learning and self-adjusting controller configured to control power supplied to the processors in response to the monitored voltage and/or current and the predicted power.