Abstract: The energy consumed by data transfer in a computing device may be reduced by transferring data that has been encoded in a manner that reduces the number of one “1” data values, the number of signal level transitions, or both. A data destination component of the computing device may receive data encoded in such a manner from a data source component of the computing device over a data communication interconnect, such as an off-chip interconnect. The data may be encoded using minimum Hamming weight encoding, which reduces the number of one “1” data values. The received data may be decoded using minimum Hamming weight decoding. For other computing devices, the data may be encoded using maximum Hamming weight encoding, which increases the number of one “1” data values while reducing the number of zero “0” values, if reducing the number of zero values reduces energy consumption.

Abstract: The energy consumed by data transfer in a computing device may be reduced by transferring data that has been encoded in a manner that reduces the number of one “1” data values, the number of signal level transitions, or both. A data destination component of the computing device may receive data encoded in such a manner from a data source component of the computing device over a data communication interconnect, such as an off-chip interconnect. The data may be encoded using minimum Hamming weight encoding, which reduces the number of one “1” data values. The received data may be decoded using minimum Hamming weight decoding. For other computing devices, the data may be encoded using maximum Hamming weight encoding, which increases the number of one “1” data values while reducing the number of zero “0” values, if reducing the number of zero values reduces energy consumption.

Abstract: A processing system includes one or more processing units to perform operations and one or more sensors to measure a temperature concurrently with the one or more processing units performing the operations. The processing system also includes a controller to receive feedback indicating the temperature and to determine a peak temperature and a thermal time constant for heating of the processing system based on a comparison of the measured temperature to a first temperature that is predicted based on the peak temperature and a previously determined thermal time constant for heating. Some embodiments of the controller can control a performance state of the processing system based on the peak temperature and the thermal time constant for heating of the processing system.

Abstract: A computing system includes a set of computing resources and a datastore to store information representing a corresponding idle power consumption metric and a corresponding peak power consumption metric for each computing resource of the set. The computing system further includes a controller coupled to the set of computing resources and the datastore. The controller is to configure the set of computing resources to meet a power budget constraint for the set based on the corresponding idle power consumption metric and the corresponding peak power consumption metric for each computing resource of the set.

Abstract: A processing system includes one or more processing units to perform operations and one or more sensors to measure a temperature concurrently with the one or more processing units performing the operations. The processing system also includes a controller to receive feedback indicating the temperature and to determine a peak temperature and a thermal time constant for heating of the processing system based on a comparison of the measured temperature to a first temperature that is predicted based on the peak temperature and a previously determined thermal time constant for heating. Some embodiments of the controller can control a performance state of the processing system based on the peak temperature and the thermal time constant for heating of the processing system.

Abstract: A computing system includes a set of computing resources and a datastore to store information representing a corresponding idle power consumption metric and a corresponding peak power consumption metric for each computing resource of the set. The computing system further includes a controller coupled to the set of computing resources and the datastore. The controller is to configure the set of computing resources to meet a power budget constraint for the set based on the corresponding idle power consumption metric and the corresponding peak power consumption metric for each computing resource of the set.

Abstract: In one form, a data processing system includes volatile and non-volatile memory, a central processing unit, and at least one peripheral device. The central processing unit executes a selected one of a plurality of software applications as directed by an operating system by transferring the selected software application from the non-volatile memory to the volatile memory and executing instructions associated with the selected software application from the volatile memory. The at least one peripheral device includes a real-time clock for defining execution contexts for the plurality of software applications. The data processing system further includes a usage pattern analyzer adapted to store history information associated with an execution context for each of the plurality of software applications, and to use the history information to direct the operating system to take at least one action based on the history information.