Abstract:
Various embodiments of methods and systems for energy efficiency aware thermal management in a portable computing device that contains a heterogeneous, multi-processor system on a chip (“SoC”) are disclosed. Because individual processing components in a heterogeneous, multi-processor SoC may exhibit different processing efficiencies at a given temperature, energy efficiency aware thermal management techniques that compare performance data of the individual processing components at their measured operating temperatures can be leveraged to optimize quality of service (“QoS”) by adjusting the power supplies to, reallocating workloads away from, or transitioning the power mode of, the least energy efficient processing components. In these ways, embodiments of the solution optimize the average amount of power consumed across the SoC to process a MIPS of workload.
Abstract:
Various embodiments of methods and systems for energy efficiency aware thermal management in a portable computing device that contains a heterogeneous, multi-processor system on a chip (“SoC”) are disclosed. Because individual processing components in a heterogeneous, multi-processor SoC may exhibit different processing efficiencies at a given temperature, energy efficiency aware thermal management techniques that compare performance data of the individual processing components at their measured operating temperatures can be leveraged to optimize quality of service (“QoS”) by adjusting the power supplies to, reallocating workloads away from, or transitioning the power mode of, the least energy efficient processing components. In these ways, embodiments of the solution optimize the average amount of power consumed across the SoC to process a MIPS of workload.
Abstract:
Various embodiments of methods and systems for energy efficiency aware thermal management in a portable computing device that contains a heterogeneous, multi-processor system on a chip (“SoC”) are disclosed. Because individual processing components in a heterogeneous, multi-processor SoC may exhibit different processing efficiencies at a given temperature, energy efficiency aware thermal management techniques that compare performance data of the individual processing components at their measured operating temperatures can be leveraged to optimize quality of service (“QoS”) by adjusting the power supplies to, reallocating workloads away from, or transitioning the power mode of, the least energy efficient processing components. In these ways, embodiments of the solution optimize the average amount of power consumed across the SoC to process a MIPS of workload.
Abstract:
A temperature of a component within the portable computing device (PCD) may be monitored along with a parameter associated with the temperature. The parameter associated with temperature may be an operating frequency, transmission power, or a data flow rate. It is determined if the temperature has exceeded a threshold value. If the temperature has exceeded the threshold value, then the temperature is compared with a temperature set point and a first error value is then calculated based on the comparison. Next, a first optimum value of the parameter is determined based on the first error value. If the temperature is below or equal to the threshold value, then a present value of the parameter is compared with a desired threshold for the parameter and a second error value is calculated based on the comparison. A second optimum value of the parameter may be determined based on the second error value.