Abstract:
Systems, methods, and computer programs are disclosed for minimizing power consumption in graphics frame processing. One such method comprises: initiating graphics frame processing to be cooperatively performed by a central processing unit (CPU) and a graphics processing unit (GPU); receiving CPU activity data and GPU activity data; determining a set of available dynamic clock and voltage/frequency scaling (DCVS) levels for the GPU and the CPU; and selecting from the set of available DCVS levels an optimal combination of a GPU DCVS level and a CPU DCVS level, based on the CPU and GPU activity data, which minimizes a combined power consumption of the CPU and the GPU during the graphics frame processing.
Abstract:
A method and system for optimizing a core voltage level of a portable computing device (“PCD”) and enhancing frequency performance of individual subcomponents are disclosed. A plurality of voltage values is determined for a plurality of subcomponents within the PCD. Next, a reduced set of voltage values may be calculated with a voltage aggregator based on the plurality of voltage values. An optimized voltage level for a shared power domain may then be determined by a voltage optimizer within the PCD from the reduced set of voltage values. A shared power domain may then be set to the optimized voltage level. Subsequently, an operating frequency of each subcomponent may be optimized with a frequency performance enhancer based on the optimized voltage level. An optimal power collapse duration may also be calculated by the frequency performance enhancer and set for each subcomponent from the optimal frequency.
Abstract:
Systems, methods, and computer programs are disclosed for dynamically adjusting memory power state transition timers. One embodiment of a method comprises receiving one or more parameters impacting usage or performance of a memory device coupled to a processor in a computing device. An optimal value is determined for one or more memory power state transition timer settings. A current value is updated for the memory power state transition timer settings with the optimal value.
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:
Systems, methods, and computer programs are provided for controlling power in a computing device. One embodiment is a system comprising a plurality of power rails coupled to one or more computing device components. Each power rail has a primary power supply for producing current at a corresponding requested voltage. The system further comprises a shared secondary power supply selectively coupled to the plurality of power rails for providing a current increase. A controller selects one of the plurality of power rails to receive the current increase. The controller generates a control signal to electrically couple the shared secondary power supply to the selected power rail to receive the current increase.
Abstract:
Systems, methods, and computer programs are disclosed for reducing leakage power of a system on chip (SoC). One such method comprises monitoring a plurality of temperature differentials across a respective plurality of thermoelectric coolers on a system on chip (SoC). Each of the thermoelectric coolers is dedicated to a corresponding one of a plurality of chip sections on the SoC. The thermoelectric coolers are controlled based on the plurality of temperature differentials to minimize a sum of a combined power consumption of the plurality of chip sections and the plurality of corresponding dedicated thermoelectric coolers.
Abstract:
Systems and methods for dynamically adjusting an input parameter to a power domain in a portable computing device are disclosed. The power domain includes two or more processing resources that share a power source. Dynamic use of the two or more processing resources creates an opportunity to adjust the input parameter when a status change associated with a processing resource in the power domain occurs. A controller in the power domain includes logic that responds to a status indicator associated with a respective processing resource in the power domain by generating a control signal that directs a device to adjust one or both of input voltage and clock frequency.
Abstract:
A method and system for optimizing a core voltage level of a portable computing device (“PCD”) and enhancing frequency performance of individual subcomponents are disclosed. A plurality of voltage values for a plurality of subsystems is determined. At least one subsystem is a multiplexed subsystem. Next, a reduced set of voltage values is calculated based on the plurality of voltage values and an optimized voltage level is determined for a shared power domain. The shared power domain is subsequently set to the optimized voltage level. If the optimized voltage level is determined to exceed a required voltage level for the at least one multiplexed subsystem when it is running the plurality of processing engines, a subset of the plurality of processing engines may be identified to process a workload of the multiplexed system at a more efficient level of power consumption than the full plurality of processing engines.
Abstract:
Neural network workload re-allocation in a system-on-chip having multiple heterogenous processors executing one or more neural network units may be based on measurements associated with the processors' conditions and on metadata associated with the neural network units. Metadata may be contained in an input file along with neural network information. Measurements characterizing operation of the processors may be obtained and compared with one or more thresholds. A neural network unit executing on a processor may be identified as a candidate for re-allocation based on metadata associated with the neural network unit and results of the comparisons. A target processor may be identified based on the metadata and results of the comparisons, and the candidate neural network neural network unit may be re-allocated to the target processor.
Abstract:
Various embodiments of methods and systems for modem management in a portable computing device are disclosed. An exemplary method recognizes an input of a key performance indicator (“KPI”) from a plurality of performance indicators. Based on the key performance indicator either manually by a user or automatically based on system status information, the exemplary method determines a particular modem management and control strategy designed to optimize performance of the modem based on the key performance indicator. The determined modem management and control strategy is implemented to cause adjustment of a modem performance level such that the key performance indicator is optimized. Exemplary KPIs include, lower device temperature, maximization of the percentage of time that the modem is operating at a maximum advertised LTE speed, maximization of the average data throughput, maximization of battery life, and minimizing LTE speed transitions over time.