System, apparatus and method for dynamically configuring one or more hardware resources of a processor

A system comprising:

• at least one processor to execute instructions;
• and
• at least one computer readable storage medium coupled to the at least one processor, the at least one computer readable storage medium comprising instructions which, when executed by the at least one processor, cause the at least one processor to:
• iteratively execute an application having a plurality of phases, each iterative execution of the application using a different set of configuration values for at least one hardware resource of a system on chip (SoC);
• maintain performance monitoring information for the plurality of phases for each iterative execution of the application;
• identify, based on an optimization cost function, an optimal set of configuration values from the different sets of configuration values for a respective phase of the plurality of phases based at least in part on the performance monitoring information, the optimal set of configuration values associated with at least one of a highest performance and a lowest power consumption for the respective phase indicated by the performance monitoring information;
• generate a machine learning model comprising the optimal set of configuration values for each of the plurality of phases, each of the optimal set of configuration values associated with one or more performance metric values;
• and
• provide the machine learning model for storage in a non-volatile memory of a plurality of SoCs to cause the plurality of SoCs to dynamically configure the one or more hardware resources of the plurality of SoCs during execution of the application.

A method comprising:

• executing, by a processor, an application having a plurality of phases identified based on a predetermined number of instructions of the application, the executing comprising iteratively executing the application with a different set of configuration values for at least one hardware resource of the processor during each iterative execution of the application;
• maintaining performance monitoring information obtained for the plurality of phases for each iterative execution of the application;
• identifying, based at least in part on instructions per cycle, an optimal set of configuration values from the different sets of configuration values for a respective phase of the plurality of phases based at least in part on the performance monitoring information, the optimal set of configuration values associated with at least one of a highest performance and a lowest power consumption for the respective phase indicated by the associated performance monitoring information;
• and
• storing the optimal set of configuration values for each of the plurality of phases in a non-volatile storage.