Hybrid system-on-chip for power and performance prediction and control

A method for predicting performance and power (PnP) requirements of a host server, the method comprising:

• receiving and pre-processing, by a big cores module of a device, PnP metrics data of the host server, the big cores module including a plurality of general purpose central processing units (CPUs);
• allocating, by the big cores module, computing resources for calculating the PnP requirements;
• mapping, by a small cores module of the device, each instance associated with host server in the PnP metrics data to a corresponding massively parallel processing (MPP) unit based on the allocated computing resources for a per-instance metric calculation, the small cores module including a plurality of MPP units;
• calculating, by an artificial intelligence (AI) accelerator of the device, PnP prediction results based on the per-instant calculations from the small cores module;
• and
• sending, by the AI accelerator, the PnP prediction results to the big cores module.

A non-transitory computer-readable storage medium storing computer-readable instructions executable by one or more processors, that when executed by the one or more processors, cause the one or more processors to perform operations comprising:

• collecting performance and power (PnP) metrics data of a host server;
• transmitting the PnP metrics data, via a host interface, to a big cores module of a device, the big cores module including a plurality of general purpose central processing units (CPUs);
• pre-processing, by the big cores module, the PnP metrics data;
• allocating, by the big cores module, computing resources for calculating the PnP requirements;
• mapping, by a small cores module of the device, each instance associated with host server in the PnP metrics data to a corresponding massively parallel processing (MPP) unit based on the allocated computing resources for a per-instance metric calculation, the small cores module including a plurality of MPP units;
• calculating, by an artificial intelligence (AI) accelerator of the device, PnP prediction results based on the per-instant calculations from the small cores module;
• sending, by the AI accelerator, the PnP prediction results to the big cores module;
• receiving, by the big cores module, the PnP prediction results from the AI accelerator;
• sending, by the big cores module, the PnP prediction to the host server via the host interface;
• and
• receiving the PnP prediction results from the big cores module.