APPARATUS AND METHOD FOR DYNAMIC MICROARCHITECTURE ADAPTION USING MACHINE LEARNING TO IMPROVE CORE PERFORMANCE

Abstract

An apparatus and method for dynamic microarchitecture adaptation based on machine learning implementations. For example, one embodiment of a method comprises: configuring a trained reinforcement learning model on a machine learning circuitry integral to a first processor of a first processor type, the trained reinforcement learning model having been trained with microarchitectural performance data and workload data corresponding to the first processor type; determining, by the machine learning circuitry using the trained reinforcement learning model, microarchitectural configuration updates based on first telemetry data and characteristics of workloads to be executed; and applying the microarchitectural configuration updates on the first processor.

CPC Classifications