Microsoft Technology Licensing, LLC

International Business Machines Corporation

Tristan Anthony Brown

Jason Stewart Wohlgemuth

Youssef M Barakat

Mark Allan Bellon

Shawn Patrick Mullen

Mehmet Iyigun

Patrick L Stemen

Nicholas Stephen Judge

Andrew Raffman

Dean L DeWhitt

Alok Gautam Kumbhare

Sandeep Prabhakar

Ricardo Gouvêa Bianchini

Omid Fatemieh

Minsang Kim

Kai-Lun Hsu

Ojasvi Choudhary

Venkat Venkatsubra

Arun Upadhyaya Kishan

Rahul Nair

Bruce Lee Worthington

Gregory Nielsen

Iulian Doroftei Calinov

Neeraj Kumar Singh

Rajagopal Venkatachalam

Arindam Chatterjee

Amit Raghunath Kulkarni

Christopher Peter Kleynhans

Abhishek Sagar

Brendan W Flynn

Cho Yu Chong

Mika Megan Latimer

Rahul Narayanan Nair

Jeremiah S Samli

Venkat Vankatsubra

Thomas Arthur Sewell

Youssef Maged Barakat

A computing device includes a cooling device and a cooling activity monitor configured to assess a cooling activity of the cooling device. A cooling activity reporter is configured to, based at least in part on the cooling activity of the cooling device crossing a predefined cooling activity threshold, communicate a cooling activity indication to a resource manager of the computing device.

Computer cooling device activity indication

Techniques of virtual machine operation management are disclosed herein. In one embodiment, a technique includes determining an operating parameter to be set for executing any processes for a virtual machine with a CPU on a server upon detecting that a process corresponding to the virtual machine hosted on the server is assigned and scheduled to be executed by a processor of the CPU. The technique can then include programming the processor of the CPU assigned to execute the process according to the operating parameter in the accessed parameter record. Upon completion of programing the one of the multiple processors, the process corresponding to the virtual machine can be executed with the processor of the CPU to achieve a target performance level associated with the virtual machine.

Virtual machine operation management in computing devices

Systems and methods for managing a power budget are provided. The method includes designating, by a power budget manager implemented on at least one processor, each of one or more applications with an individual quality of service (QoS) designation, the one or more applications executable by the at least one processor, assigning, by the power budget manager, a throttling priority to each of the one or more applications based on the individual QoS designations, determining, by the power budget manager, whether a platform mitigation threshold is exceeded, and responsive to determining that the platform mitigation threshold is exceeded, throttling, by the power budget manager, processing power allocated to at least one application of the one or more applications based on the throttling prioritization.

Power budget management using quality of service (QoS)

Techniques of virtual machine operation management are disclosed herein. In one embodiment, a technique includes determining an operating parameter to be set for executing any processes for a virtual machine with a CPU on a server upon detecting that a process corresponding to the virtual machine hosted on the server is assigned and scheduled to be executed by a processor of the CPU. The technique can then include programming the processor of the CPU assigned to execute the process according to the operating parameter in the accessed parameter record. Upon completion of programming the one of the multiple processors, the process corresponding to the virtual machine can be executed with the processor of the CPU to achieve a target performance level associated with the virtual machine.

Embodiments are directed to capturing and storing historical data regarding thermal remediations, to predicting and acting on remediation futures and to communicating with applications regarding thermal remediations implemented on the computer system. In one scenario, a computer system determines which thermal remediations are currently being implemented on a monitored computing device. The thermal remediations are based on the monitored computing device's current operating environment including the physical thermal environment and/or the current software execution environment. The computer system further tracks thermal remediation levels for those thermal remediations that are currently being implemented on the monitored computing device, the thermal remediation levels indicating the degree to which each thermal remediation is implemented. The computer system also filters the tracked thermal remediation levels for tracked thermal remediation information that includes information regarding the computing device's current operating environment, and stores the filtered thermal remediation levels in a data store.

Implementing thermal remediations in reaction to execution of software

Each processor core in a computing device supports various different frequency ranges, also referred to as p-states, and can operate to run threads at any one of those different frequency ranges. Threads in the computing device are assigned one of multiple importance levels. A processor core is configured to run at a particular frequency range or in accordance with a particular energy performance preference based on the importance level of the thread it is running. A utilization factor of a processor core can also be determined over some time duration, the utilization factor being based on the amount of time during the time duration that the processor core was running a thread(s), and also based on the importance levels of the thread(s) run during the time duration. The utilization factor can then be used to determine whether to park the processor core.

Thread importance based processor core parking and frequency selection

Each processor core in a device supports various different frequency ranges and/or energy performance preferences, and can operate to run threads at any one of those different frequency ranges and/or energy performance preferences. Processor cores are partitioned into different groups, each group running at different frequency ranges and/or energy performance preferences. Threads in the device are assigned one of multiple importance levels and scheduled to run on a processor core in a particular group based on the importance level of the thread. Lower importance level threads are scheduled to run in a group that is more power efficient, and higher importance level threads are scheduled to run in a group that is higher performance. The group that a processor core is part of can change during operation of the device based on the needs of the device and/or applications running on the device.

Thread importance based processor core partitioning

An operating system includes an interrupt router that dynamically steers each interrupt to one or more processors within set of processors based on overall load information from the set of processors. An interrupt source is assigned to a processor based on the load imposed by the interrupt source and the target overall load for the processor. For example, each processor can maintain information about each interrupt it processes over time. The operating system receives this historical load information to determine an expected load for interrupts of a given type from a given device, an overall load on the system, and a target load for each processor. Given a set of interrupt sources, their expected loads, and target load for each processor, each interrupt source can be assigned dynamically to a processor during runtime of the system. These assignments can be changed given current operating conditions of the system.

Operating system-managed interrupt steering in multiprocessor systems

In embodiments of an idle time service, it can be determined that processing on a device is in an idle state. An execution duration of applications that are scheduled to be executed by a processor of the device can then be extended to reduce power consumption by the device. In other embodiments, it can be determined that an application configured to execute on a device is a background application. The execution duration of the background application can then be extended to reduce power consumption by the device.

Idle time service

Heterogeneous thread scheduling techniques are described in which a processing workload is distributed to heterogeneous processing cores of a processing system. The heterogeneous thread scheduling may be implemented based upon a combination of periodic assessments of system-wide power management considerations used to control states of the processing cores and higher frequency thread-by-thread placement decisions that are made in accordance with thread specific policies. In one or more implementations, a system workload context is periodically analyzed for a processing system having heterogeneous cores including power efficient cores and performance oriented cores. Based on the periodic analysis, cores states are set for some of the heterogeneous cores to control activation of the power efficient cores and performance oriented cores for thread scheduling. Then, individual threads are scheduled in dependence upon the core states to allocate the individual threads between active cores of the heterogeneous cores on a per-thread basis.

Heterogeneous thread scheduling

An operating system is provided in which an interrupt router dynamically steers each interrupt to one or more processors within set of processors based on overall load information from the set of processors. An interrupt source is assigned to a processor based on the load imposed by the interrupt source and the target overall load for the processor. For example, each processor can maintain information about each interrupt it processes over time. The operating system receives this historical load information to determine an expected load for interrupts of a given type from a given device, an overall load on the system, and a target load for each processor. Given a set of interrupt sources, their expected loads, and target load for each processor, each interrupt source can be assigned dynamically to a processor during runtime of the system. On a regular basis, these assignments can be changed given current operating conditions of the system.

One or more techniques and/or systems are provided for dynamically applying power policies to a computing environment. For example, a computing environment may comprise one or more activity components (e.g., a display driver, an audio driver, an application, etc.) that may provide status information used to identify a scenario (e.g., a video game scenario, a full screen video playback scenario, etc.) that is activated for the computing environment. A power policy assigned to a currently identified scenario may be applied to the computing environment to dynamically improve performance and/or power conservation, for example. Activity components, scenarios, and/or power policies may be maintained in an extensible manner such that activity components, scenarios, and/or power polices may be added, removed, and/or modified by merely updating corresponding data structures, such as tables or registry keys, as opposing to updating power management software code.

Scenario power management

A mechanism is provided for identifying a snooping device in a network environment. A snoop echo response extractor generates an echo request packet with a bogus MAC address that will only be received by a snooping device. The snoop echo response extractor also uses an IP address that will cause the snooping device to respond to the echo request.

Snoop echo response extractor

Systems and methods that automatically generate remediation processes such as acts performed as part of a benchmark model, to improve and update compliance of a machine with security policies compliance. A remediation component can automatically determine processes that are required to change and increase compliance of a machine with a security policy, and hence improve security level thereof.

Growing community of inventors

Bellevue, WA, United States of America

Tristan Anthony Brown