Abstract: Examples include a computing system for receiving memory class of service parameters; setting performance monitoring configuration parameters, based at least in part on the memory class of service parameters, for use by a performance monitor of a memory controller to generate performance monitoring statistics by monitoring performance of one or more workloads by a plurality of processor cores based at least in part on the performance monitoring configuration parameters; receiving the performance monitoring statistics from the performance monitor; and generating, based at least in part on the performance monitoring statistics, a plurality of memory bandwidth settings to be applied by a memory bandwidth allocator to the plurality of processor cores to dynamically adjust priorities of memory bandwidth allocated for the one or more workloads to be processed by the plurality of processor cores.

Abstract: Examples described herein relate to circuitry to utilize a proportional, derivative, integral neural network (PIDNN) controller to adjust one or more parameters allocated to a first group of one or more workloads based on one or more target parameters for a second group of one or more workloads. In some examples, the second group of one or more workloads are a same, lower, or higher priority level than that of the first group of one or more workloads.

Abstract: Hierarchical Power Management (HPM) architecture considers the limits of scaling on a power management controller, the autonomy at each die, and provides a unified view of the package to a platform. At a simplest level, HPM architecture has a supervisor and one or more supervisee power management units (PMUs) that communicate via at least two different communication fabrics. Each PMU can behave as a supervisor for a number of supervisee PMUs in a particular domain. HPM addresses these needs for products that comprise a collection of dice with varying levels of power and thermal management capabilities and needs. HPM serves as a unified mechanism than can span collection of dice of varying capability and function, which together form a traditional system-on-chip (SoC). HPM provides a basis for managing power and thermals across a diverse set of dice.

Abstract: Examples include a computing system for receiving memory class of service parameters; setting performance monitoring configuration parameters, based at least in part on the memory class of service parameters, for use by a performance monitor of a memory controller to generate performance monitoring statistics by monitoring performance of one or more workloads by a plurality of processor cores based at least in part on the performance monitoring configuration parameters; receiving the performance monitoring statistics from the performance monitor; and generating, based at least in part on the performance monitoring statistics, a plurality of memory bandwidth settings to be applied by a memory bandwidth allocator to the plurality of processor cores to dynamically adjust priorities of memory bandwidth allocated for the one or more workloads to be processed by the plurality of processor cores.