Dynamic energy performance preference based on workloads using an adaptive algorithm

A machine-readable storage media having machine-executable instructions, that when executed, cause one or more machines to perform operations comprising:

• receiving telematic data and performance data from one or more hardware components;
• providing the telematic data and performance data to a machine-learning engine to predict a workload type;
• receiving the predicted workload type;
• adaptively modifying an energy performance preference based on the predicted workload type;
• and
• providing the modified energy performance preference to a firmware which in turn adjusts frequency and/or voltage of the one or more components.

A system comprising:

• a memory;
• a processor coupled to the memory;
• a wireless interface communicatively coupled to the processor, wherein the processor includes a power control unit which executes a firmware that adaptively adjusts an energy performance preference for one or more hardware components of the system, including the processor, based on parameters including predicted workload and usage behavior of applications executed on the one or more hardware components;
• and
• a machine-learning engine communicatively coupled to the firmware, wherein the machine-learning engine predicts a workload type based on telematic data from the one or more hardware components.

A method comprising:

• receiving telematic data and performance data from one or more hardware components;
• providing the telematic data and performance data to a machine-learning engine to predict a workload type;
• receiving the predicted workload type;
• adaptively modifying an energy performance preference based on the predicted workload type;
• and
• providing the modified energy performance preference to a firmware which in turn adjusts frequency and/or voltage of the one or more components.