Intel Corporation

Muhammad Abozaed

Eugene Gorbatov

Avinash N Ananthakrishnan

Gaurav Khanna

Songnan Yang

Hong W Wong

James G Hermerding, Ii

David Gomez Gutierrez

Rafael De La Guardia Gonzalez

Efraim Rotem

Atsuo Kuwahara

Russell Jerome Fenger

Tod F Schiff

Alexander Uan-Zo-Li

Chee Lim Nge

Rajshree Chabukswar

Ahmad A Samih

Monica Gupta

Sudheer Nair

Alexander B Uan-Zo-li

Vijay Dhanraj

Shadi T Khasawneh

Mukund Ramakrishna

Avishai Wagner

Ido Karavany

Patrick Kam-Shing Leung

Tahi Hollander

Guruprasad Settuvalli

Gilad Olswang

Moran Peri

William Freelove

Christine M Lin

James G Ii Hermerding

Embodiments are generally directed to enhanced power management for support of priority system events. An embodiment of a system includes a processing element; a memory including a registry for information regarding one or more system events that are designated as priority events; a mechanism to track operation of events that requires Turbo mode operation for execution; and a power control unit to implement a power management algorithm. The system is to maintain an first energy budget and a second residual energy budget for operation in a Turbo power mode, and wherein the power management algorithm is to determine whether to authorize execution of a detected system event in the Turbo power mode based on the second residual energy budget upon determining that the first energy budget is not sufficient for execution of the detected system event and that the detected system event is designated as a priority event. Priority designations for the priority events may include a first High Priority designation and a second Critical designation.

Enhanced power management for support of priority system events

The present disclosure is directed to dynamically prioritizing, selecting or ordering a plurality threads for execution by processor circuitry based on a quality of service and/or class of service value/indicia assigned to the thread by an operating system executed by the processor circuitry. As threads are executed by processor circuitry, the operating system dynamically updates/associates respective class of service data with each of the plurality of threads. The current quality of service/class of service data assigned to the thread by the operating system is stored in a manufacturer specific register (MSR) associated with the respective thread. Selection circuitry polls the MSRs on a periodic, aperiodic, intermittent, continuous, or event-driven basis and determines an execution sequence based on the current class of service value associated with each of the plurality of threads.

Operating system assisted prioritized thread execution

In one embodiment, a method receives data regarding processing of a workload by a processor. The data is input into a prediction engine configured to classify the data into a plurality of workload classifications. Each workload classification describes different temporal behavior of the workload. Then, the method outputs a prediction for at least one of the plurality of workload classifications, wherein the prediction is used to control performance of the processor in an upcoming period of time.

Classification prediction of workload thermal behavior

Methods and apparatus for reducing energy consumed by drones during flight are disclosed. A drone includes a housing, a motor, receiver circuitry carried by the housing, and a route manager. The receiver circuitry is to receive airborne drone-generated wind data from an airborne drone located in an area within which a segment of a flight of the drone is to occur. The airborne drone-generated wind data is to be determined by an inertial measurement unit of the airborne drone. The route manager is to generate a route for the flight of the drone based on wind data, the wind data including the airborne drone-generated wind data. The route is to be followed by the drone during the flight. The route manager is to select at least one portion of the route to cause the drone to be at least partially propelled by wind to reduce energy consumed by the drone during the flight.

Methods and apparatus for reducing energy consumed by drones during flight

In some examples, a peak power system includes a plurality of system components, one or more of the system components to dynamically provide a peak power requirement of the component. The system also includes a peak power manager to receive the peak power requirement of the one or more of the system components. The peak power manager can also dynamically provide, based on a system peak power limit and based on at least one updated peak power requirement received from at least one of the one or more system components, an updated component peak power limit to one or more of the system components.

Power management and protection

Methods and apparatus for reducing energy consumed by drones during flight are disclosed. A drone includes a housing, a motor, and a route manager to generate a route for a flight of the drone based on wind data. The wind data includes turbine-generated wind data provided by turbines that detect airflows received at the turbines. The turbines are located in an area within which a segment of the flight of the drone is to occur. The route is to be followed by the drone during the flight to reduce energy consumed by the drone during the flight.

Growing community of inventors

Haifa, Israel

Muhammad Abozaed