Abstract: Example implementations and techniques are described in which a processor uses a dynamic adjustment algorithm, including algorithms based on performance and energy models, to readjust frequency settings for a graphics processing unit (GPU), and independently for a system memory or for a system memory bus, to an optimal level for meeting sustained performance requirements with the low level of power consumption.

Abstract: Example implementations and techniques are described in which a processor uses a dynamic adjustment algorithm, including algorithms based on performance and energy models, to readjust frequency settings for a graphics processing unit (GPU), and independently for a system memory or for a system memory bus, to an optimal level for meeting sustained performance requirements with the low level of power consumption.

Abstract: At least one processor may determine, for each of a plurality of operating performance points (OPPs) that each comprise a memory frequency and a graphics processing unit (GPU) frequency, an estimated energy consumption associated with a memory and the GPU operating at the respective memory frequency and GPU frequency to process a workload based at least in part on a plurality of energy equations associated with the plurality of OPPs. The at least one processor may set the memory and the GPU to operate at the respective memory frequency and GPU frequency of one of the plurality of OPPs to process the workload based at least in part on the estimated energy consumption.