Abstract: 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.

Abstract: In examples, a device configuration is evaluated according to a set of conservation rules, such that one or more configuration recommendations may be generated. A configuration recommendation may be presented to a user of the computing device, such that the user may accept or reject the recommendation. If the recommendation is rejected, the recommendation may be presented to the user at a later time. In another example, a sustainability forecast may be obtained by the computing device, which may include estimated characteristics for an associated energy grid. The sustainability forecast may be presented to a user, thereby enabling the user to consider whether it may be preferable to use the computing device in one or more time periods that have a comparatively lower estimated environmental impact. A sustainability utilization metric may also be generated that is indicative of an estimated past environmental impact of the device.

Abstract: 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.

Abstract: 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.

Abstract: Disclosed is a system (100) and a method (200) for computing compatibility ranked list using intelligent capability matrix. The intelligent capability matrix comprises a set of pre-defined parameters that considers demonstrated capabilities to distinguish, identify and validate aspects of capabilities and complexities, for example, for an employer and a candidate. The method (200) performs intelligent mapping of skills and experience of the candidate to a capability grid of the employer followed by quantification of the intelligent mapping between the candidate and role requirements to find a best match between them. The intelligent mapping allocates differential weights to various set of aspects of the employer and the candidate based on historical data. The system (100) and the method (200) is time and cost effective and reduces dependency on resume and JD.

Abstract: Usage data of a device is maintained over some time period, such as a couple weeks or a couple months. This usage data reflects an amount of energy that is used or stored for different time durations each having a various combinations of different state values of the device, such as a screen state, a power source state, a power mode state, a battery saver state, a processor consumption state, and so forth. This provides a record of a capacity drain rate or capacity charge rate for the battery for each combination of state values. At any given time, the device can determine the current state values of the device. The capacity drain rates or capacity charge rates for previous time durations having the same state values as the current state values are used to determine an estimated capacity drain rate or capacity charge rate for the device.

Abstract: A computing device has an energy storage device system with one or more energy storage devices. A target run-time is obtained, which refers to how long the computing device is to run given the current amount of energy in the energy storage device(s). A predicted power usage over the target run-time is determined, and what, if any, power management actions to take in order to achieve the target run-time are determined. The power management actions are then taken. A target charge-time is also obtained, which refers to how long the computing device is to take to charge the energy storage device(s) to a threshold level (e.g., 100% or fully charged). A predicted power gain over the target charge-time is determined, and what, if any, power management actions to take in order to achieve the target charge-time are determined. The power management actions are then taken.

Abstract: Embodiments relate to enabling software to interface with a power consumption telemetry system. A process may have tagging instructions that interface with an energy estimation engine. While the energy estimation engine is logging energy consumption by the process, the process may also mark, tag, or otherwise delineate periods of processing during the execution time of the process. The logic of the process may determine how such periods should be labeled and when they being and end. The tagged periods are correlated with energy consumed by the process so that details of what the process was doing during different periods of energy consumption may be understood.

Abstract: Consumption of power by device components is profiled on a per-session basis of user interaction. A session engine determines start of a user interaction session with the device (e.g., by detecting screen turn on). The engine generates a session identifier (SID) and broadcasts same to device component(s). In response to the SID, the component(s) record power consumption data. Upon receiving a signal indicating end of the user interaction session (e.g., screen turn off), the session engine broadcasts a notice allowing component(s) to stop recording power consumption data. The components communicate aggregated data to the session engine for storage in a centralized location (e.g., trace buffer). In response to a query posed within a command line prompt, stored data may be parsed on a per-session basis for inclusion in a detailed report of power consumption. Power consumption inefficiencies endemic to components and/or user behaviors may be thus be identified and remediated.

Abstract: A computing device has an energy storage device system with one or more energy storage devices. A target run-time is obtained, which refers to how long the computing device is to run given the current amount of energy in the energy storage device(s). A predicted power usage over the target run-time is determined, and what, if any, power management actions to take in order to achieve the target run-time are determined. The power management actions are then taken. A target charge-time is also obtained, which refers to how long the computing device is to take to charge the energy storage device(s) to a threshold level (e.g., 100% or fully charged). A predicted power gain over the target charge-time is determined, and what, if any, power management actions to take in order to achieve the target charge-time are determined. The power management actions are then taken.

Abstract: Consumption of power by device components is profiled on a per-session basis of user interaction. A session engine determines start of a user interaction session with the device (e.g., by detecting screen turn on). The engine generates a session identifier (SID) and broadcasts same to device component(s). In response to the SID, the component(s) record power consumption data. Upon receiving a signal indicating end of the user interaction session (e.g., screen turn off), the session engine broadcasts a notice allowing component(s) to stop recording power consumption data. The components communicate aggregated data to the session engine for storage in a centralized location (e.g., trace buffer). In response to a query posed within a command line prompt, stored data may be parsed on a per-session basis for inclusion in a detailed report of power consumption. Power consumption inefficiencies endemic to components and/or user behaviors may be thus be identified and remediated.

Abstract: Embodiments relate to enabling software to interface with a power consumption telemetry system. A process may have tagging instructions that interface with an energy estimation engine. While the energy estimation engine is logging energy consumption by the process, the process may also mark, tag, or otherwise delineate periods of processing during the execution time of the process. The logic of the process may determine how such periods should be labeled and when they being and end. The tagged periods are correlated with energy consumed by the process so that details of what the process was doing during different periods of energy consumption may be understood.

Abstract: Analyzing energy consumption of one or more computer systems based on gathered telemetry data. Telemetry data is accessed from computer systems. The telemetry data includes parameters, each associated with a data type. The telemetry data is organized into data sets that each include at least one of the parameters. Each data set is associated with one computer system, and includes an energy consumption parameter indicative of an amount of energy used. The data sets are organized into data set clusters based on the at least one parameter included in each data set. For each cluster, each data set that satisfies an energy consumption threshold associated with further analyzing the data set to determine a cause of the energy amount used may be identified. The identified data sets are analyzed to find patterns associated with the at least one parameter that are likely cause of the amount of energy used.

Abstract: Usage data of a device is maintained over some time period, such as a couple weeks or a couple months. This usage data reflects an amount of energy that is used or stored for different time durations each having a various combinations of different state values of the device, such as a screen state, a power source state, a power mode state, a battery saver state, a processor consumption state, and so forth. This provides a record of a capacity drain rate or capacity charge rate for the battery for each combination of state values. At any given time, the device can determine the current state values of the device. The capacity drain rates or capacity charge rates for previous time durations having the same state values as the current state values are used to determine an estimated capacity drain rate or capacity charge rate for the device.

Abstract: Embodiments described herein relate to improving throughput of a CPU and a GPU working in conjunction to render graphics. Time frames for executing CPU and GPU work units are synchronized with a refresh rate of a display. Pending CPU work is performed when a time frame starts (a vsync occurs). When a prior GPU work unit is still executing on the GPU, then a parallel mode is entered. In the parallel mode, some GPU work and some CPU work is performed concurrently. When the parallel mode is exited, for example when there is no CPU work to perform, the parallel mode may be exited.

Abstract: The specification describes a technique for drawing circular core multimode optical fiber using twist during draw to increase fiber bandwidth.

Abstract: The specification describes a technique for drawing circular core multimode optical fiber using twist during draw to increase fiber bandwidth.

Abstract: The specification describes a technique for drawing circular core multimode optical fiber using twist during draw to increase fiber bandwidth.

Abstract: The specification describes a technique for drawing circular core multimode optical fiber using twist during draw to increase fiber bandwidth.