公开(公告)号：US20140189710A1

公开(公告)日：2014-07-03

申请号：US14195976

申请日：2014-03-04

Applicant: QUALCOMM INCORPORATED

Inventor： Sumit SUR ,  James M. Artmeier ,  Mark D. Guzzi ,  Philip T. Mueller ,  Bohuslav Rychlik

IPC: G06F9/50

CPC classification number: G06F9/5094 ,  G06F1/206 ,  G06F1/329 ,  G06F1/3293 ,  G06F11/3058 ,  G06F11/3433 ,  Y02D10/122 ,  Y02D10/16 ,  Y02D10/22 ,  Y02D10/24 ,  Y02D10/34

Abstract: Various embodiments of methods and systems for thermally aware scheduling of workloads 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, and because more than one of the processing components may be capable of processing a given block of code, thermally aware workload scheduling techniques that compare performance curves of the individual processing components at their measured operating temperatures can be leveraged to optimize quality of service (“QoS”) by allocating workloads in real time, or near real time, to the processing components best positioned to efficiently process the block of code.

Abstract translation: 公开了在包含芯片上的异构多处理器系统（“SoC”）的便携式计算设备中用于热感知调度工作负载的方法和系统的各种实施例。 由于异构多处理器SoC中的单独处理组件可能在给定温度下可能表现出不同的处理效率，并且由于多个处理组件可能能够处理给定的代码块，因此热感知工作负载调度技术可以比较性能 可以利用其测量的工作温度下的各个处理组件的曲线，以便通过实时或接近实时地将工作负载分配给最佳定位以有效地处理代码块的处理组件来优化服务质量（“QoS”）。

公开(公告)号：US09442774B2

公开(公告)日：2016-09-13

申请号：US14195976

申请日：2014-03-04

Applicant: QUALCOMM INCORPORATED

Inventor： Sumit Sur ,  James M. Artmeier ,  Mark D. Guzzi ,  Philip T. Mueller, Jr. ,  Bohuslav Rychlik

IPC: G06F9/46 ,  G06F9/455 ,  G06F9/50 ,  G06F1/20 ,  G06F1/32 ,  G06F11/30 ,  G06F11/34

CPC classification number: G06F9/5094 ,  G06F1/206 ,  G06F1/329 ,  G06F1/3293 ,  G06F11/3058 ,  G06F11/3433 ,  Y02D10/122 ,  Y02D10/16 ,  Y02D10/22 ,  Y02D10/24 ,  Y02D10/34

Abstract: Various embodiments of methods and systems for thermally aware scheduling of workloads 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, and because more than one of the processing components may be capable of processing a given block of code, thermally aware workload scheduling techniques that compare performance curves of the individual processing components at their measured operating temperatures can be leveraged to optimize quality of service (“QoS”) by allocating workloads in real time, or near real time, to the processing components best positioned to efficiently process the block of code.