Abstract: A processing unit of a processing system compiles a priority queue listing of a plurality of processor cores to run a workload based on a cost of running the workload on each of the processor cores. The cost is based on at least one of a system usage policy, characteristics of the workload, and one or more physical constraints of each processor core. The processing unit selects a processor core based on the cost to run the workload and communicates an identifier of the selected processor core to an operating system of the processing system.

Abstract: Platform power management includes boosting performance in a platform power boost mode or restricting performance to keep a power or temperature under a desired threshold in a platform power cap mode. Platform power management exploits the mutually exclusive nature of activities and the associated headroom created in a temperature and/or power budget of a server platform to boost performance of a particular component while also keeping temperature and/or power below a threshold or budget.

Abstract: Platform power management includes boosting performance in a platform power boost mode or restricting performance to keep a power or temperature under a desired threshold in a platform power cap mode. Platform power management exploits the mutually exclusive nature of activities and the associated headroom created in a temperature and/or power budget of a server platform to boost performance of a particular component while also keeping temperature and/or power below a threshold or budget.

Abstract: An apparatus includes a processor, a sleep state duration prediction module, and a system management unit. The sleep state duration prediction module is configured to predict a sleep state duration for component of the processing device. The system management unit is to transition the component into a sleep state selected from a plurality of sleep states based on a comparison of the predicted sleep state duration to at least one duration threshold. Each sleep state of the plurality of sleep states is a lower power state than a previous sleep state of the plurality of sleep states.

Abstract: An apparatus includes a processor, a sleep state duration prediction module, and a system management unit. The sleep state duration prediction module is configured to predict a sleep state duration for component of the processing device. The system management unit is to transition the component into a sleep state selected from a plurality of sleep states based on a comparison of the predicted sleep state duration to at least one duration threshold. Each sleep state of the plurality of sleep states is a lower power state than a previous sleep state of the plurality of sleep states.

Abstract: An apparatus includes a processor, a sleep state duration prediction module, and a system management unit. The sleep state duration prediction module is configured to predict a sleep state duration for component of the processing device. The system management unit is to transition the component into a sleep state selected from a plurality of sleep states based on a comparison of the predicted sleep state duration to at least one duration threshold. Each sleep state of the plurality of sleep states is a lower power state than a previous sleep state of the plurality of sleep states.

Abstract: Methods and apparatus employ a plurality of heterogeneous compute units and a plurality of non-compute units operatively coupled to the plurality of compute units. Power management logic (PML) determines a memory bandwidth level associated with a respective workload running on each of a plurality of heterogeneous compute units on the IC, and adjusts a power level of at least one non-compute unit of a memory system on the IC from a first power level to a second power level, based on the determined memory bandwidth levels. Memory access latency is also taken into account in some examples to adjust a power level of non-compute units.

Abstract: Methods and apparatus manage data in memories disposed in a stacked relation with respect to one or more processors. The method includes receiving at least one hint indicating future processor usage of a software component, where the future processor usage is indicative of future usage of the one or more processors when executing the software component or a code section of the software component. In some implementations, the method includes selecting a memory location in the memories for data used by the software component based on the hint.

Abstract: A processing unit of a processing system compiles a priority queue listing of a plurality of processor cores to run a workload based on a cost of running the workload on each of the processor cores. The cost is based on at least one of a system usage policy, characteristics of the workload, and one or more physical constraints of each processor core. The processing unit selects a processor core based on the cost to run the workload and communicates an identifier of the selected processor core to an operating system of the processing system.

Abstract: Platform power management includes boosting performance in a platform power boost mode or restricting performance to keep a power or temperature under a desired threshold in a platform power cap mode. Platform power management exploits the mutually exclusive nature of activities and the associated headroom created in a temperature and/or power budget of a server platform to boost performance of a particular component while also keeping temperature and/or power below a threshold or budget.

Abstract: Platform power management includes boosting performance in a platform power boost mode or restricting performance to keep a power or temperature under a desired threshold in a platform power cap mode. Platform power management exploits the mutually exclusive nature of activities and the associated headroom created in a temperature and/or power budget of a server platform to boost performance of a particular component while also keeping temperature and/or power below a threshold or budget.

Abstract: A power management algorithm framework proposes: 1) a Quality-of-Service (QoS) metric for throughput-based workloads; 2) heuristics to differentiate between throughput and latency sensitive workloads; and 3) an algorithm that combines the heuristic and QoS metric to determine target frequency for minimizing idle time and improving power efficiency without any performance degradation. A management algorithm framework enables optimizing power efficiency in server-class throughput-based workloads while still providing desired performance for latency sensitive workloads. The power savings are achieved by identifying workloads in which one or more cores can be run at a lower frequency (and consequently lower power) without a significant negative performance impact.

Abstract: A method and apparatus for managing power in a thermal couple aware system includes determining a candidate configuration mapping based upon one or more criteria, the candidate configuration mapping being a mapping of performance for a candidate configuration of processor sockets in the thermal couple aware system. The candidate configuration mapping is evaluated by comparing the candidate configuration mapping to a stored configuration. If the evaluated candidate configuration mapping provides a better metric than the stored configuration, the stored configuration is updated with the evaluated candidate configuration mapping, and programming instructions are executed in accordance with the candidate configuration mapping if no other configuration mappings are to be determined.

Abstract: A processing unit includes a plurality of subsystem control modules. Each subsystem control module includes a set of one or more inputs that receives a set of one or more external signals and a set of one or more monitored outputs from a hardware subsystem corresponding to the subsystem control module, and a set of configuration outputs for controlling one or more configuration settings of the hardware subsystem. The subsystem control module determines the one or more configuration settings based on the set of monitored outputs and on one or more targets derived from the set of external signals.

Abstract: Platform power management includes boosting performance in a platform power boost mode or restricting performance to keep a power or temperature under a desired threshold in a platform power cap mode. Platform power management exploits the mutually exclusive nature of activities and the associated headroom created in a temperature and/or power budget of a server platform to boost performance of a particular component while also keeping temperature and/or power below a threshold or budget.

Abstract: Techniques for managing power distribution amongst processors in a massively parallel computer architecture are disclosed. The techniques utilize a hierarchy that organizes the various processors of the massively parallel computer architecture. The hierarchy groups numbers of the processors at the lowest level. When processors complete tasks, the power assigned to those processors is distributed to other processors in the same group so that the performance of those processors can be increased. Hierarchical organization simplifies the calculations required for determining how and when to distribute power, because when tasks are complete and power is available for distribution, a relatively small number of processors are available for consideration to receive that power. The number of processors that are grouped together can be adjusted in real time based on performance factors to improve the trade-off between calculation speed and power distribution efficacy.

Abstract: A processing unit includes a plurality of subsystem control modules. Each subsystem control module includes a set of one or more inputs that receives a set of one or more external signals and a set of one or more monitored outputs from a hardware subsystem corresponding to the subsystem control module, and a set of configuration outputs for controlling one or more configuration settings of the hardware subsystem. The subsystem control module determines the one or more configuration settings based on the set of monitored outputs and on one or more targets derived from the set of external signals.

Abstract: A power management algorithm framework proposes: 1) a Quality-of-Service (QoS) metric for throughput-based workloads; 2) heuristics to differentiate between throughput and latency sensitive workloads; and 3) an algorithm that combines the heuristic and QoS metric to determine target frequency for minimizing idle time and improving power efficiency without any performance degradation. A management algorithm framework enables optimizing power efficiency in server-class throughput-based workloads while still providing desired performance for latency sensitive workloads. The power savings are achieved by identifying workloads in which one or more cores can be run at a lower frequency (and consequently lower power) without a significant negative performance impact.

Abstract: Techniques for managing power distribution amongst processors in a massively parallel computer architecture are disclosed. The techniques utilize a hierarchy that organizes the various processors of the massively parallel computer architecture. The hierarchy groups numbers of the processors at the lowest level. When processors complete tasks, the power assigned to those processors is distributed to other processors in the same group so that the performance of those processors can be increased. Hierarchical organization simplifies the calculations required for determining how and when to distribute power, because when tasks are complete and power is available for distribution, a relatively small number of processors are available for consideration to receive that power. The number of processors that are grouped together can be adjusted in real time based on performance factors to improve the trade-off between calculation speed and power distribution efficacy.

Abstract: Methods, devices, and systems for capturing an accuracy of an instruction executing on a processor. An instruction may be executed on the processor, and the accuracy of the instruction may be captured using a hardware counter circuit. The accuracy of the instruction may be captured by analyzing bits of at least one value of the instruction to determine a minimum or maximum precision datatype for representing the field, and determining whether to adjust a value of the hardware counter circuit accordingly. The representation may be output to a debugger or logfile for use by a developer, or may be output to a runtime or virtual machine to automatically adjust instruction precision or gating of portions of the processor datapath.