Core Frequency Management using Effective Utilization for Power-Efficient Performance
US-2019004585-A1 · Jan 3, 2019 · US
US2019094941A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2019094941-A1 |
| Application number | US-201715713254-A |
| Country | US |
| Kind code | A1 |
| Filing date | Sep 22, 2017 |
| Priority date | Sep 22, 2017 |
| Publication date | Mar 28, 2019 |
| Grant date | — |
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A method of operating a shared resource in a mobile device includes extracting a set of features from a plurality of subsystems of the mobile device. The set of features may be extracted from each subsystem of the plurality of subsystems requesting services from one or more shared resources of the mobile device. One or more parameter of the shared resource(s) may be determined based on the extracted set of features from the plurality of subsystems. The shared resource(s) may be operated based on the determined parameter(s).
Opening claim text (preview).
What is claimed is: 1 . A method of operating a shared resource in a mobile device, comprising: extracting a set of features from a plurality of subsystems of the mobile device, each subsystem of the plurality of subsystems requesting services from at least one shared resource of the mobile device; determining at least one parameter of the at least one shared resource based on the extracted set of features from the plurality of subsystems; and operating the at least one shared resource based on the at least one parameter. 2 . The method of claim 1 , further comprising processing a workload from the plurality of subsystems. 3 . The method of claim 1 , wherein the at least one parameter is learned based at least in part on a performance metric associated with a workload and power consumption of the mobile device. 4 . The method of claim 1 , wherein the at least one parameter is learned based at least in part on a cumulative reward, the cumulative reward comprising a combination of measured performance associated with a workload and power consumption for processing a sequence of predetermined workloads. 5 . The method of claim 1 , wherein the at least one shared resource comprises a processor and the extracted set of features includes at least one of a current processor frequency, a number of instructions to be executed by the processor, a processor utilization, a measured bandwidth, or a ratio thereof. 6 . An apparatus of operating a shared resource in a mobile device, comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured to: extract a set of features from a plurality of subsystems of the mobile device, each subsystem of the plurality of subsystems requesting services from at least one shared resource of the mobile device; determine at least one parameter of the at least one shared resource based on the extracted set of features from the plurality of subsystems; and operate the at least one shared resource based on the at least one parameter. 7 . The apparatus of claim 6 , wherein the at least one processor is further configured to process a workload from the plurality of subsystems. 8 . The apparatus of claim 6 , wherein the at least one processor is further configured to learn the at least one parameter based at least in part on a performance metric associated with a workload and power consumption of the mobile device. 9 . The apparatus of claim 6 , wherein the at least one processor is further configured to learn the at least one parameter based at least in part on a cumulative reward, the cumulative reward comprising a combination of measured performance associated with a workload and power consumption for processing a sequence of predetermined workloads. 10 . The apparatus of claim 6 , wherein the at least one shared resource comprises a processor and the extracted set of features includes at least one of a current processor frequency, a number of instructions to be executed by the processor, a processor utilization, a measured bandwidth, or a ratio thereof. 11 . An apparatus for operating a shared resource in a mobile device, comprising: means for extracting a set of features from a plurality of subsystems of the mobile device, each subsystem of the plurality of subsystems requesting services from at least one shared resource of the mobile device; means for determining at least one parameter of the at least one shared resource based on the extracted set of features from the plurality of subsystems; and means for operating the at least one shared resource based on the at least one parameter. 12 . The apparatus of claim 11 , further comprising means for processing a workload from the plurality of subsystems. 13 . The apparatus of claim 11 , further comprising means for learning the at least one parameter based at least in part on a performance metric associated with a workload and power consumption of the mobile device. 14 . The apparatus of claim 11 , further comprising means for learning the at least one parameter based at least in part on a cumulative reward, the cumulative reward comprising a combination of measured performance associated with a workload and power consumption for processing a sequence of predetermined workloads. 15 . The apparatus of claim 11 , wherein the at least one shared resource comprises a processor and the extracted set of features includes at least one of a current processor frequency, a number of instructions to be executed by the processor, a processor utilization, a measured bandwidth, or a ratio thereof. 16 . A computer-readable medium storing computer executable code for operating a shared resource in a mobile device, comprising code to: extract a set of features from a plurality of subsystems of the mobile device, each subsystem of the plurality of subsystems requesting services from at least one shared resource of the mobile device; determine at least one parameter of the at least one shared resource based on the extracted set of features from the plurality of subsystems; and operate the at least one shared resource based on the at least one parameter. 17 . The computer-readable medium of claim 16 , further comprising code to process a workload from the plurality of subsystems. 18 . The computer-readable medium of claim 16 , further comprising code learn the at least one parameter based at least in part on a performance metric associated with a workload and power consumption of the mobile device. 19 . The computer-readable medium of claim 16 , further comprising code to learn the at least one parameter based at least in part on a cumulative reward, the cumulative reward comprising a combination of measured performance associated with a workload and power consumption for processing a sequence of predetermined workloads. 20 . The computer-readable medium of claim 16 , wherein the at least one shared resource comprises a processor and the extracted set of features includes at least one of a current processor frequency, a number of instructions to be executed by the processor, a processor utilization, a measured bandwidth, or a ratio thereof.
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