Abstract: A robot operates using electrical power. An application subsystem provides application functionality such as processing speech, performing video calls, retrieving information responsive to a user request, presenting audio or video content, and so forth. A mobility subsystem includes sensors, software, and hardware that allows the robot to move about an environment. The application subsystem operates using electrical power from a first battery while the mobility subsystem operates using electrical power from a second battery. An electrical interconnect allows for the transfer of electrical power between the subsystems. A power management module uses information about previous tasks performed by the robot that involved the application subsystem and the mobility subsystem to develop power training data. This power training data is then used to estimate power consumption for future task requests.

Abstract: Methods, systems, and computer program products are provided for supervised power management between a primary platform and a secondary platform. Communication between a primary platform and a secondary platform is established. An application running on the secondary platform is captured. Input features and output measures are collected to build a training set for the application, wherein the input features are collected through direct measurement and the output measures reflect characteristics of the application. Based on the training set, power consumption of the secondary platform with an expected performance level is predicted for a new application running on the secondary platform. Accordingly, an optimal power management policy is derived that minimizes the total power consumption of the primary and secondary platforms.

Abstract: Methods, systems, and computer program products are provided for supervised power management between a primary platform and a secondary platform. Communication between a primary platform and a secondary platform is established. An application running on the secondary platform is captured. Input features and output measures are collected to build a training set for the application, wherein the input features are collected through direct measurement and the output measures reflect characteristics of the application. Based on the training set, power consumption of the secondary platform with an expected performance level is predicted for a new application running on the secondary platform. Accordingly, an optimal power management policy is derived that minimizes the total power consumption of the primary and secondary platforms.

Abstract: Methods, systems, and computer program products are provided for supervised power management between a primary platform and a secondary platform. Communication between a primary platform and a secondary platform is established. An application running on the secondary platform is captured. Input features and output measures are collected to build a training set for the application, wherein the input features are collected through direct measurement and the output measures reflect characteristics of the application. Based on the training set, power consumption of the secondary platform with an expected performance level is predicted for a new application running on the secondary platform. Accordingly, an optimal power management policy is derived that minimizes the total power consumption of the primary and secondary platforms.

Abstract: Systems and methods are presented for reducing the impact of high load and aging on processor cores in a processor. A Power Management Unit (PMU) can monitor aging, temperature, and increased load on the processor cores. The PMU instructs the processor to take action such that aging, temperature, and/or increased load are approximately evenly distributed across the processor cores, so that the processor can continue to efficiently process instructions.

Abstract: A system and method are provided to improve power efficiency of processor cores, such as processor cores in a multicore processor. A break-even time of a processor core may be determined that affects which power saving mode a processor core should enter when an expected idle of the processor core is identified. The break-even time of the processor core may be determined during run-time to help determine an applicable power saving mode that improves power efficiency of the processor core.

Abstract: A processor arrangement changes its default time interval for entering a power saving mode based on sensed operating conditions and predetermined time intervals to be used under various operating conditions to optimize power saving.

Abstract: System and method for incrementally varying input levels and recording respective output temperatures at the varied levels, storing, in a training table, first correlations between the varied levels of the input parameter and defined temperature ranges, detecting an input parameter level during operation and re-recording the output temperature at the detected level, generating a second correlation between the detected level and a second temperature range, determining whether the second temperature range is different from a first temperature range from among the defined temperature ranges, the first temperature range correlating to the level of the input parameter corresponding to the detected level, updating the training table when the second temperature range is different from the first temperature range, predicting an expected temperature range, and dynamically scaling, based on the expected temperature range, the detected level of the input parameter to control the output temperature in real-time.

Abstract: A semiconductor device includes a memory storing a lookup table including stored values associated with modes of operation of a component of the semiconductor device. A monitor monitors an operating parameter of the component in real-time, and reports a calculated value associated with the same. A power manager determines a change in the mode of operation of the component based on a comparison of the calculated value with a corresponding stored value, and adjusts a current mode of operation of the component in real-time.

Abstract: A semiconductor device includes a memory storing a lookup table including stored values associated with modes of operation of a component of the semiconductor device. A monitor monitors an operating parameter of the component in real-time, and reports a calculated value associated with the same. A power manager determines a change in the mode of operation of the component based on a comparison of the calculated value with a corresponding stored value, and adjusts a current mode of operation of the component in real-time.

Abstract: Methods, systems, and computer program products are provided for supervised power management between a primary platform and a secondary platform. Communication between a primary platform and a secondary platform is established. An application running on the secondary platform is captured. Input features and output measures are collected to build a training set for the application, wherein the input features are collected through direct measurement and the output measures reflect characteristics of the application. Based on the training set, power consumption of the secondary platform with an expected performance level is predicted for a new application running on the secondary platform. Accordingly, an optimal power management policy is derived that minimizes the total power consumption of the primary and secondary platforms.

Abstract: System and method for incrementally varying input levels and recording respective output temperatures at the varied levels, storing, in a training table, first correlations between the varied levels of the input parameter and defined temperature ranges, detecting an input parameter level during operation and re-recording the output temperature at the detected level, generating a second correlation between the detected level and a second temperature range, determining whether the second temperature range is different from a first temperature range from among the defined temperature ranges, the first temperature range correlating to the level of the input parameter corresponding to the detected level, updating the training table when the second temperature range is different from the first temperature range, predicting an expected temperature range, and dynamically scaling, based on the expected temperature range, the detected level of the input parameter to control the output temperature in real-time.

Abstract: A system and method are provided to improve power efficiency of processor cores, such as processor cores in a multicore processor. A break-even time of a processor core may be determined that affects which power saving mode a processor core should enter when an expected idle of the processor core is identified. The break-even time of the processor core may be determined during run-time to help determine an applicable power saving mode that improves power efficiency of the processor core.

Abstract: A processor arrangement changes its default time interval for entering a power saving mode based sensed operating conditions and predetermined time intervals to be used under various operating conditions to optimize power saving.

Abstract: A semiconductor device includes a memory storing a lookup table including stored values associated with modes of operation of a component of the semiconductor device. A monitor monitors an operating parameter of the component in real-time, and reports a calculated value associated with the same. A power manager determines a change in the mode of operation of the component based on a comparison of the calculated value with a corresponding stored value, and adjusts a current mode of operation of the component in real-time.

Abstract: Systems and methods are presented for reducing the impact of high load and aging on processor cores in a processor. A Power Management Unit (PMU) can monitor aging, temperature, and increased load on the processor cores. The PMU instructs the processor to take action such that aging, temperature, and/or increased load are approximately evenly distributed across the processor cores, so that the processor can continue to efficiently process instructions.

Abstract: Embodiments of the present disclosure provide systems and methods for proactively managing power in a device. A power management unit (PMU) receives information from various subsystems of a device and estimates the total power required by each subsystem of the device. Based on this information, the PMU can predict power requirements for a particular subsystem or for one or more application(s) to execute. Based on this prediction, the PMU can reconfigure the subsystems so that the device executes more efficiently given the current battery life of the device. Proactive power management advantageously gives the PMU the capability to predict power needs of various subsystems of a device so that the power supplied to these subsystems can be managed in an intelligent way before battery resources are exhausted.