CN110737322B - Information processing method and electronic equipment - Google Patents
Information processing method and electronic equipment Download PDFInfo
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- CN110737322B CN110737322B CN201910869814.1A CN201910869814A CN110737322B CN 110737322 B CN110737322 B CN 110737322B CN 201910869814 A CN201910869814 A CN 201910869814A CN 110737322 B CN110737322 B CN 110737322B
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- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3234—Power saving characterised by the action undertaken
- G06F1/3243—Power saving in microcontroller unit
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- G—PHYSICS
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- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
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Abstract
The embodiment of the application discloses an information processing method and electronic equipment. The information processing method can comprise the following steps: acquiring first historical state information of a processing module; determining the working state of the processing module according to the first historical state information; determining a power control parameter of the processing module according to the working state; and controlling the power consumption of the processing module according to the power control parameter.
Description
Technical Field
The present invention relates to the field of information technologies, and in particular, to an information processing method and an electronic device.
Background
Electronic devices (e.g., notebook computers) and the like each include a Central Processing Unit (CPU). The CPU is one of the main components within the electronic device that consumes electrical energy. Various schemes for achieving power consumption and performance optimization of CPUs have been proposed in the related art.
The method I comprises the following steps: the performance of the CPU is improved or the Power consumption of the CPU is reduced by increasing or decreasing Thermal Design Power (TDP) parameters of the CPU.
The second method comprises the following steps: a list of Application programs (APP) is established, but the APP in the list is operated by the equipment, and the operation parameters of the CPU are adaptively set, so that the purpose of optimizing the performance of the CPU or reducing the power consumption of the CPU is achieved.
However, in the first mode, the CPU generally has only one set of fixed TDP parameters, and the performance optimization of the CPU as a whole or the power consumption reduction of the CPU are limited, and obviously, the performance optimization of the CPU or the power consumption minimization of the CPU cannot be realized in most cases. And establishing an App list according to the second mode, wherein if the App is renamed or updated, the optimal TDP parameter of the corresponding App in the App list may be changed, and the performance optimization of the CPU or the power consumption minimization of the CPU cannot be realized.
Disclosure of Invention
In view of this, embodiments of the present invention are directed to an information processing method and an electronic device.
The technical scheme of the invention is realized as follows:
a first aspect of an embodiment of the present application provides an information processing method, including:
acquiring first historical state information of a processing module;
determining the working state of the processing module according to the first historical state information;
determining a power control parameter of the processing module according to the working state;
and controlling the power consumption of the processing module according to the power control parameter.
Based on the above scheme, the method further comprises:
and determining the condition parameter of the working state according to second historical state information, wherein the second historical state information comprises the first historical state information, or the second historical state information is acquired before the first historical state information.
Based on the above scheme, the determining the condition parameter of the working state according to the second historical state information includes:
learning the second historical state information based on a machine learning algorithm to obtain the condition parameters;
or,
and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.
Based on the above scheme, the acquiring of the first historical state information of the processing module includes at least one of:
acquiring historical power consumption information of the processing module, wherein the historical power consumption information comprises: historical power consumption values and/or historical power consumption fluctuation values of the processing module;
acquiring historical frequency information of the processing module, wherein the historical frequency information comprises: and the historical frequency value and/or the historical frequency fluctuation value of the processing module.
Based on the above scheme, the condition parameter includes at least one of the following:
a frequency threshold;
a frequency fluctuation threshold;
a power consumption threshold;
a power fluctuation threshold.
Based on the above scheme, determining the working state of the processing module according to the first historical state information includes one of:
when the frequency of the processing module is determined to be lower than a first frequency threshold value according to the first historical state information, and the power consumption of the processing module is determined to be lower than a first power consumption threshold value, determining that the processing module is in a first state;
when the frequency of the processing module is determined to be higher than the first frequency threshold and lower than a second frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the first power consumption threshold and lower than a second power consumption threshold, determining that the electronic equipment is in a second state; wherein the second frequency threshold is higher than the first frequency threshold; the second power consumption threshold is higher than the first power consumption threshold;
when the frequency of the processing module is determined to be higher than the second frequency threshold and lower than a third frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the second power consumption threshold and lower than a third power consumption threshold, determining that the processing module is in a third state; wherein the third frequency threshold is higher than the second frequency threshold; the third power consumption threshold is higher than the second power consumption threshold;
when the frequency fluctuation value of a processing module in the electronic equipment is determined to be higher than a first frequency variance threshold value according to the first historical state information, and the power consumption fluctuation value of the processing module is determined to be higher than a first power consumption fluctuation threshold value, determining that the processing module is in a fourth state;
and when the processing module is determined to be in a state other than the first state to the fourth state according to the first historical state information, determining that the processing module is in a fifth state.
Based on the above scheme, the determining the power control parameter of the processing module according to the operating state includes:
determining a first power control parameter of the processing module when the processing module is in the first state, the second state, or the third state;
and when the processing module is in the fourth state or the fifth state, determining a second power control parameter of the processing module, wherein the power consumption of the processing module when working with the second power control parameter is larger than the power consumption of the processing module when working with the first power control parameter.
Based on the above scheme, the power control parameter includes at least one of:
the first power consumption parameter is used for indicating the fluctuation range of the average power consumption of the processing module;
a second power consumption parameter for indicating a maximum instantaneous power consumption value of the processing module.
Based on the above scheme, the method further comprises:
determining whether the electronic device is in a power saving mode;
the acquiring of the first historical state information of the processing module includes:
and when the power consumption saving mode is in, acquiring the first historical state information of the processing module.
A second aspect of embodiments of the present application provides an electronic device, including:
the acquisition module is used for acquiring first historical state information of the processing module;
the first determining module is used for determining the working state of the processing module according to the first historical state information;
the second determining module is used for determining the power control parameter of the processing module according to the working state;
and the control module is used for controlling the power consumption of the processing module according to the power control parameter.
According to the information processing method and the electronic device provided by the embodiment of the invention, the first historical state information of the processing module can be dynamically acquired, then the working state of the processing module is determined according to the first historical state information, the power control parameter of the processing module is determined based on the working state, and finally the function is performed on the processing module based on the power control parameter, so that the power control of the processing module can be realized. In the process of determining the working state of the processing module, the state information of the processing module is dynamically acquired, and is not determined according to the currently running application program, so that even if the application program in the electronic equipment is installed, uninstalled and upgraded, the working state of the processing module cannot be negatively influenced, and the method has the characteristic of high working state determination accuracy of the processing module. Finally, a power control parameter is given by combining the working state to control the power of the processing module, and on the first hand, the power consumption requirement of most parts of the processing module can be met; in the second aspect, the waste of power caused by excessive supply can be reduced; in the third aspect, the processing module can obtain power actually through power control, and the resource configuration of the processing module can be realized, so that the resource optimal configuration of the processing module in work is realized. In the fourth aspect, compared with the scheme of collecting and recording the habits of the user, the first historical state information of the processing module is directly collected and recorded, the type and the quantity of the information to be collected are reduced, the collected and recorded data volume and the information processing amount for determining the working state are reduced, so that the operation of the electronic equipment is simplified, and excessive extra load caused by the division of the working state of the processing module is reduced.
Drawings
Fig. 1 is a schematic flowchart of a first information processing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a second information processing method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a third information processing method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 5 is a flowchart illustrating a fourth information processing method according to an embodiment of the present application.
Detailed Description
The technical solution of the present invention is further described in detail with reference to the drawings and the specific embodiments of the specification.
As shown in fig. 1, the present embodiment provides an information processing method, including:
s110: acquiring first historical state information of a processing module;
s120: determining the working state of the processing module according to the first historical state information;
s130: determining a power control parameter of the processing module according to the working state;
s140: and controlling the power consumption of the processing module according to the power control parameter.
The information processing method provided by the embodiment of the application is applied to various electronic devices. The electronic devices include, but are not limited to: notebook computer, desktop computer, panel computer, notebook panel two-in-one and wearable equipment etc..
The electronic devices include, but are not limited to: mobile devices and stationary devices. The mobile devices include, but are not limited to: vehicle-mounted equipment and man-mounted equipment.
The processing module may be a Central Processing Unit (CPU) or a Graphics Processing Unit (GPU).
The first historical state information of the processing module may include: the actual power consumption value of the processing module and the working frequency of the processing module.
The first historical state information may be: status information of the processing module before the current time.
In the embodiment of the application, the first historical state information is carried out, and the working state of the processing module is determined. In this embodiment, the operating states of the processing modules may be divided into multiple types.
The power control parameter is used for controlling the power consumption of the processing module.
In an embodiment of the present application, the power control parameter may include at least one of:
the first type of power control parameters can be used for controlling the average power of the processing module within a preset time period;
and the second type of power control parameters can be used for controlling the instantaneous power of the processing module within a preset time period.
In some cases, the first type of power control parameter is used to define a power range, which may include: maximum power and minimum power.
The second type of power control parameter is an instantaneous power, which may be greater than an average power, so in some cases, the second type of power control parameter may be greater than an upper limit of the first type of power control parameter.
In the embodiment of the application, the working state of the processing module is determined directly according to the actual state parameters of the processing modules such as the CPU, and the determination mode of the working state has the characteristic of high accuracy.
After the working state of the processing module is judged, power control parameters can be configured for the processing module according to the current working state of the processing module. And then, providing power to the processing module according to the power control parameter, thereby realizing the power control of the processing module. For example, the power supply module is controlled to supply power to the processing module according to the power control parameter. The power module includes, but is not limited to, a battery of the electronic device.
Utilize this kind of mode control to handle the operating condition of module, for confirming the operating condition that the Application scene confirmed the processing module according to the white list of Application (Application, APP), can reduce the operation of APP and receive the inaccuracy phenomenon that disturbs and the environment acts on the processing module and leads to. Meanwhile, the phenomenon that due to the fact that information technology is developed, new APP is introduced, the APP is upgraded, the name of the APP or the number of the APP is changed, the information of the white list is incomplete or inaccurate, and the work state of the processing module is inaccurate is determined.
In an embodiment of the present application, the working state of the processing module is dynamically determined, for example, a first historical state parameter of the processing module is collected in real time. In S120, the operating state of the processing module may be determined in real time based on the first historical power consumption parameter. For example, a first historical state parameter of the processing module is collected in real time, and then the working state of the processing module is judged once based on the first historical state parameter in a time period. In summary, in the embodiment of the present application, the working state of the processing module is dynamically determined, and the working state of the processing module can be known in time.
The power consumption actually obtained by the processing module may adversely affect the frequency of the processing module, for example, when the actual power consumption obtained by the processing module is not enough to support the high-frequency operation of the processing module, the processing module may perform a down-conversion process. The frequency of the processing module is related to the actual power consumption of the processing module, for example, the higher the operating frequency of the general processing module is, the higher the actual power consumption of the processing module is.
In the embodiment of the application, the working state of the processing module is determined according to the first historical state information before the current moment of the processing module. Then, a power control parameter is given in combination with the working state to control the power of the processing module, and on the first hand, the power consumption requirement of most parts of the processing module can be met; in the second aspect, the waste of power caused by excessive supply can be reduced; in the third aspect, the processing module can obtain power actually through power control, and the resource configuration of the processing module can be realized, so that the resource optimal configuration of the processing module in work is realized. In the fourth aspect, compared with the scheme of collecting and recording user habits, the first historical state information of the processing module is directly collected and recorded, the type and the quantity of information to be collected are reduced, the data volume to be collected and recorded and the information processing amount for determining the working state are reduced, so that the operation of the electronic equipment is simplified, and excessive extra load caused by the division of the working state of the processing module per se is reduced.
In some embodiments, determining the operating state of the processing module according to the first historical state information in S120 uses a determination condition for determining the operating state of the processing module.
In some embodiments, the condition parameters involved in determining the condition are determined dynamically.
In some embodiments, as shown in fig. 2, the method further comprises:
s100: and determining the condition parameter of the working state according to second historical state information, wherein the second historical state information comprises the first historical state information, or the second historical state information is acquired before the first historical state information.
As such, the S120 may include: and determining the working state of the processing module according to the condition parameters and the first historical state information.
In this embodiment, the second historical state information is also acquired parameters of the actual state of the processing module.
In some application embodiments, the second historical state information may include the first historical state information, e.g., the second historical state information is equal to the first historical state parameter, or the second historical state information includes the first historical state information and state information prior to the first historical state information.
In still other embodiments, the second historical state information may include: history state information prior to the first history state information, and at this time, the second history state information does not include the first history state information.
The working state of the processing module is assumed to be determined every N seconds; the condition parameters are determined every M seconds, and if M is larger than X times of N, M, N and X are positive integers. If X is greater than 2, it is determined that the second historical state information of the condition parameter may not include the first historical state information.
In some embodiments, the working state of the processing module is updated according to a first period, and the condition parameter is updated according to a second period, wherein the second period is greater than or equal to the first period.
And P types of working states are preset in the working state of the electronic equipment, the actual working state of the processing module is corresponding to the P types of states according to the second historical state information of the processing module, and the condition parameters for dividing any two of the P types of states are determined. P is a positive integer of 2 or more, such as 2 or 3.
In this way, different electronic devices have the same operating state, but due to the difference of the second historical state information, the condition parameters for dividing the same operating state are different. Thus, the condition parameters can be related to the working environment of the electronic equipment, the use habits of users and the self configuration of the equipment, and can be adapted to the self condition of the electronic equipment.
The work environment includes, but is not limited to: at least one of the working temperature, the working noise and the working brightness.
The user using habits comprise: the time period that the user uses the electronic equipment, the application type that the user prefers to use, the specific application that the user prefers to use and the function of the electronic equipment that the user prefers to use.
The self-configuration of the electronic device may include: hardware configuration and/or software configuration of an electronic device. The hardware configuration may include: the number of cpu cores included in the electronic device, the heat dissipation power of the heat dissipation assembly, and the like. The heat dissipation assembly includes: a fan for air cooling and heat radiation and/or a heat radiation bag for liquid cooling and heat radiation.
In some embodiments, the determining the condition parameter of the operating state according to the second historical state information includes:
learning the second historical state information based on a machine learning algorithm to obtain the condition parameters;
or,
and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.
In the embodiment of the present application, the condition parameters for dividing the operating states of the processing modules are dynamically determined.
And a machine learning algorithm is operated in the electronic equipment, and can analyze the second historical state information, then the second historical state information is corresponding to the P working states, and then the corresponding relation between the second historical state information and the P working states is used for determining condition parameters for dividing the P working states.
For example, in some embodiments, the second historical state information is analyzed using an inductive learning algorithm of a machine learning algorithm to obtain the condition parameter.
In some embodiments, the condition parameters of the P operating states are also determined by learning the second historical state information using a deep learning algorithm. The deep learning algorithm includes, but is not limited to, a neural network.
In some embodiments, the S110 may include at least one of:
acquiring historical power consumption information of the processing module, wherein the historical power consumption information comprises: historical power consumption values and/or historical power consumption fluctuation values of the processing modules;
acquiring historical frequency information of the processing module, wherein the historical frequency information comprises: and the historical frequency value and/or the historical frequency fluctuation value of the processing module.
For example, the historical power consumption values may include: and actual power consumption values at each time are collected in real time, and the actual power consumption values can be sequenced to form an actual power consumption value sequence.
In some embodiments, the historical power consumption fluctuation value may be a power consumption variance value obtained by performing variance calculation according to the collected historical power consumption value, so as to reflect the historical power consumption fluctuation.
In other embodiments, the historical power consumption fluctuation value may be further: based on the difference between the minimum actual power consumption value and the maximum power consumption value over a period of time.
In some embodiments, the method further comprises:
identifying user identity information using the electronic device;
acquiring storage condition parameters according to the user identity information;
in the subsequent operation process of the electronic equipment, updating the condition parameters corresponding to the user identity information according to the second historical state information of the processing module during operation, so that when a user corresponding to the user identity information again uses the electronic equipment next time, determining the power control parameters of the processing module in the electronic equipment, and controlling the power of the processing module.
For example, the electronic device is an electronic device common to the user a and the user B.
When the electronic equipment is started, whether the current user is a user A or a user B is identified so as to acquire the user identity information of the current user. For example, the user identity information is determined by image acquisition and then face recognition of the acquired image. For another example, the user identity information is determined by voice acquisition, then acoustic feature extraction is performed on the acquired voice, and then the user identity information is determined based on the extracted acoustic features. The acoustic features include, but are not limited to, voiceprint features.
After identifying the user identity information, inquiring condition parameters corresponding to the user identity information, and taking the inquired condition parameters as initial condition parameters determined for the working state of the processing module. Subsequently, second historical state information of the processing module is collected according to the actual operation of the electronic equipment, the inquired condition parameters are updated, and if the condition parameters are updated, the condition parameters corresponding to the user identity information are updated correspondingly.
Therefore, even if the electronic equipment is a public equipment, the condition parameters may be different when the working state of the processing module is judged based on the identification of the user identity information, so that the judgment of the working state of the processing module can be matched with the current condition of the electronic equipment, and the optimization of the power control of the processing module is ensured.
In some embodiments, the condition parameter comprises at least one of:
a frequency threshold;
a frequency fluctuation threshold;
a power consumption threshold;
a power fluctuation threshold.
In some embodiments, the S120 may include one of:
when the frequency of the processing module is determined to be lower than a first frequency threshold value according to the first historical state information, and the power consumption of the processing module is determined to be lower than a first power consumption threshold value, determining that the processing module is in a first state;
when the frequency of the processing module is determined to be higher than the first frequency threshold and lower than a second frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the first power consumption threshold and lower than a second power consumption threshold, determining that the electronic equipment is in a second state; wherein the second frequency threshold is higher than the first frequency threshold; the second power consumption threshold is higher than the first power consumption threshold;
when the frequency of the processing module is determined to be higher than the second frequency threshold and lower than a third frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the second power consumption threshold and lower than a third power consumption threshold, determining that the processing module is in a third state; wherein the third frequency threshold is higher than the second frequency threshold; the third power consumption threshold is higher than the second power consumption threshold;
when the frequency fluctuation value of a processing module in the electronic equipment is higher than a first frequency variance threshold value and the power consumption fluctuation value of the processing module is higher than a first power consumption fluctuation threshold value according to the first historical state information, determining that the processing module is in a fourth state;
and when the processing module is determined to be in a state other than the first state to the fourth state according to the first historical state information, determining that the processing module is in a fifth state.
In the embodiment of the present application, the working state of the processing module is defined as 5, and these 5 states can more comprehensively cover various application scenarios of the processing module.
In some embodiments, the S130 may include:
determining a first power control parameter of the processing module when the processing module is in the first state, the second state, or the third state;
and when the processing module is in the fourth state or the fifth state, determining a second power control parameter of the processing module, wherein the power consumption of the processing module working with the second power control parameter is larger than the power consumption of the processing module working with the first power control parameter.
In some embodiments, the power control parameter comprises at least one of:
a first power consumption parameter indicating a fluctuation range of an average power consumption of the processing module;
a second power consumption parameter for indicating a maximum instantaneous power consumption value of the processing module.
In some embodiments, after determining the power control parameter, the power control module provides power to the processing module according to the power control parameter, so as to implement power control of the processing module. And the power optimization and the performance optimization of the processing module are realized through the power control of the processing module.
In some embodiments, as shown in fig. 3, the method further comprises:
s101: determining whether the electronic device is in a power saving mode;
the S110 may include: and when the power consumption saving mode is in, acquiring the state information of the processing module.
The electronic device has a power saving mode and a normal power consumption mode other than the power saving mode. If the electronic device enters the power saving mode after being started based on the user operation or the configuration operation, the information processing method from S110 to S140 is performed.
As shown in fig. 4, this embodiment further provides an electronic device, including:
an obtaining module 110, configured to obtain first historical state information of a processing module;
a first determining module 120, configured to determine a working state of the processing module according to the first historical state information;
a second determining module 130, configured to determine a power control parameter of the processing module according to the working state;
and the control module 140 is configured to control power consumption of the processing module according to the power control parameter.
In some embodiments, the acquisition module 110, the first determination module 120, the second determination module 130, and the control module 140 may be program modules; after being executed by the processor, the program module can realize the acquisition of the first historical state information, the determination of the working state, the determination of the power control parameter and the power consumption control of the processing module.
In other embodiments, the obtaining module 110, the first determining module 120, the second determining module 130, and the control module 140 may be a combination of hardware and software modules, including but not limited to a programmable array; the programmable array includes, but is not limited to: complex programmable arrays and field programmable arrays.
In some embodiments, the apparatus further comprises:
a third determining module, configured to determine a condition parameter of the working state according to second historical state information, where the second historical state information includes the first historical state information, or the second historical state information is obtained before the first historical state information.
In some embodiments, the third determining module is specifically configured to perform one of:
learning the second historical state information based on a machine learning algorithm to obtain the condition parameters;
or,
and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.
In some embodiments, the obtaining module 110110 is specifically configured to execute at least one of the following:
obtaining historical power consumption information of the processing module, wherein the historical power consumption information comprises: historical power consumption values and/or historical power consumption fluctuation values of the processing modules;
acquiring historical frequency information of the processing module, wherein the historical frequency information comprises: and the historical frequency value and/or the historical frequency fluctuation value of the processing module.
In some embodiments, the condition parameter comprises at least one of:
a frequency threshold;
a frequency fluctuation threshold;
a power consumption threshold;
a power fluctuation threshold.
In some embodiments, the first determining module 120 is specifically configured to perform one of:
when the frequency of the processing module is determined to be lower than a first frequency threshold value according to the first historical state information, and the power consumption of the processing module is determined to be lower than a first power consumption threshold value, determining that the processing module is in a first state;
when the frequency of the processing module is determined to be higher than the first frequency threshold and lower than a second frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the first power consumption threshold and lower than a second power consumption threshold, determining that the electronic equipment is in a second state; wherein the second frequency threshold is higher than the first frequency threshold; the second power consumption threshold is higher than the first power consumption threshold;
when the frequency of the processing module is determined to be higher than the second frequency threshold and lower than a third frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the second power consumption threshold and lower than a third power consumption threshold, determining that the processing module is in a third state; wherein the third frequency threshold is higher than the second frequency threshold; the third power consumption threshold is higher than the second power consumption threshold;
when the frequency fluctuation value of a processing module in the electronic equipment is determined to be higher than a first frequency variance threshold value according to the first historical state information, and the power consumption fluctuation value of the processing module is determined to be higher than a first power consumption fluctuation threshold value, determining that the processing module is in a fourth state;
and when the processing module is determined to be in a state other than the first state to the fourth state according to the first historical state information, determining that the processing module is in a fifth state.
In some embodiments, the second determining module 130 is specifically configured to perform one of:
determining a first power control parameter of the processing module when the processing module is in the first state, the second state, or the third state;
and when the processing module is in the fourth state or the fifth state, determining a second power control parameter of the processing module, wherein the power consumption of the processing module working with the second power control parameter is larger than the power consumption of the processing module working with the first power control parameter.
In some embodiments, the power control parameter comprises at least one of:
a first power consumption parameter indicating a fluctuation range of an average power consumption of the processing module;
a second power consumption parameter for indicating a maximum instantaneous power consumption value of the processing module.
In some embodiments, the apparatus further comprises: a third determining module for determining whether the electronic device is in a power saving mode;
the obtaining module 110 is specifically configured to obtain the first historical state information of the processing module when the processing module is in the power saving mode.
Several specific examples are provided below in connection with any of the embodiments described above:
example 1:
a machine learning algorithm (ML) is adopted, real-time power consumption, frequency and other input information of a CPU are utilized, and a proper machine learning algorithm, such as a data intensive induction learning algorithm, is adopted to output condition parameters for distinguishing 5 working states of the CPU.
For example, the 5 states may be: a first state, a second state, a third state, a fourth state and a fifth state. The first state may also be referred to as an idle state; the second state may be a light load state, which may be referred to as a battery life state (battery life), the third state may be a heavy load continuous state, which may be referred to as a sustain state (sustain), the fourth state may be a heavy load burst state, which may be referred to as a (burst), and the fifth state may be other states than the first to fourth states. This fifth state may also be referred to as a semi-active state. These 5 states may cover all possible operating states of the CPU, i.e. all CPU states at the time of APP run.
Each electronic device or each electronic device includes the 5 states in different periods, but different condition parameters for distinguishing the states are set according to parameters such as power consumption, frequency and the like of actual operation of the CPU. For these 5 states, the (DPTF) parameters of the CPU for these 5 scenarios can be debugged, so as to provide the running performance of the CPU and reduce the unnecessary power consumption of the CPU at the same time.
According to the technical scheme provided by the example, the intelligent optimization coverage scene is wide, the workload in the research and development stage is reduced, the machine learning algorithm can be upgraded, and the goal of automatically learning the behavior habits of the user is achieved.
Example 2:
as shown in fig. 5, the present example provides an information processing method, which may include:
electronic device startup, after which monitoring software (e.g., Vantage) is started;
after the monitoring software is started, whether the electronic equipment selects to enter a power consumption saving mode is judged, if the electronic equipment is not in the power consumption saving mode, a machine learning mechanism is not executed, under the machine learning mechanism, the electronic equipment can determine the working state of the CUP based on the condition parameters of machine learning, and according to the determined working state of the CPU, the corresponding power consumption parameter is selected to control the power consumption of the CPU. And if the electronic equipment is in the power consumption saving mode, obtaining condition parameters for dividing different working states of the CPU by using an inductive learning algorithm according to the CUP real-time power consumption and the CPU real-time frequency.
In fig. 5, the CPU is configured with five states, which are a first state/a second state (battery life state/idle state), a third state (heavy load maintenance state), a fourth state (heavy load burst state), and a fifth state (semi-active state).
The condition parameters for distinguishing the 5 states may be A1W, A2Hz, B1W, B2Hz, C1W, and C2Hz shown in fig. 5.
The first three states adopt a set of DPTF parameters, which are stored in a DPTF file 1 and respectively include: the Power is limited to maximum (Power Limit 1max, PL1max), (Power Limit 1min, PL1max), and (Power Limit2, PL 2). PL1 max-PL 1 min-5W located in DPTF file 1 as shown in fig. 5; PL 2-12W.
The latter two states may share a set of DPTF parameters, which are stored in DPTF file 2 and respectively include: PL1max, PL1min and PL 2. PL1max ═ PL1min ═ 8W located in DPTF file 2 as shown in fig. 5; PL 2-25W.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
Technical features disclosed in any embodiment of the present application may be combined arbitrarily to form a new method embodiment or an apparatus embodiment without conflict.
The method embodiments disclosed in any embodiment of the present application can be combined arbitrarily to form a new method embodiment without conflict.
The device embodiments disclosed in any embodiment of the present application can be combined arbitrarily to form a new device embodiment without conflict.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a specific implementation of the present example, but the protection scope of the present example is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present example, and should be covered within the protection scope of the present example. Therefore, the protection scope of the present example shall be subject to the protection scope of the claims.
Claims (9)
1. An information processing method, comprising:
acquiring first historical state information and second historical state information of a processing module; the first historical state information is the state information of the processing module before the current moment; the second historical state information is acquired before the first historical state information;
determining a condition parameter according to the second historical state information; the condition parameters are related to the working environment of the electronic equipment, the use habits of a user and the self configuration of the electronic equipment;
dynamically determining the working state of the processing module according to the first historical state information and the condition parameters; the working state comprises a plurality of types, and can cover various application scenes of the processing module;
determining a power control parameter for controlling the power consumption of the processing module according to the working state based on the mapping relation between the working state and the power control parameter;
and controlling the power consumption of the processing module according to the power control parameter.
2. The method of claim 1, wherein said determining a condition parameter of said operating state based on second historical state information comprises:
learning the second historical state information based on a machine learning algorithm to obtain the condition parameters;
or,
and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.
3. The method of claim 1 or 2,
the acquiring of the first historical state information of the processing module includes at least one of:
acquiring historical power consumption information of the processing module, wherein the historical power consumption information comprises: historical power consumption values and/or historical power consumption fluctuation values of the processing module;
acquiring historical frequency information of the processing module, wherein the historical frequency information comprises: and the historical frequency value and/or the historical frequency fluctuation value of the processing module.
4. The method of claim 1 or 2, wherein the condition parameter comprises at least one of:
a frequency threshold;
a frequency fluctuation threshold;
a power consumption threshold;
a power fluctuation threshold.
5. The method of claim 1 or 2,
determining the working state of the processing module according to the first historical state information, wherein the working state comprises one of the following:
when the frequency of the processing module is determined to be lower than a first frequency threshold value according to the first historical state information, and the power consumption of the processing module is determined to be lower than a first power consumption threshold value, determining that the processing module is in a first state;
when the frequency of the processing module is determined to be higher than the first frequency threshold and lower than a second frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the first power consumption threshold and lower than a second power consumption threshold, determining that the electronic equipment is in a second state; wherein the second frequency threshold is higher than the first frequency threshold; the second power consumption threshold is higher than the first power consumption threshold;
when the frequency of the processing module is determined to be higher than the second frequency threshold and lower than a third frequency threshold according to the first historical state information, and the power consumption of the processing module is determined to be higher than the second power consumption threshold and lower than a third power consumption threshold, determining that the processing module is in a third state; wherein the third frequency threshold is higher than the second frequency threshold; the third power consumption threshold is higher than the second power consumption threshold;
when the frequency fluctuation value of a processing module in the electronic equipment is higher than a first frequency variance threshold value and the power consumption fluctuation value of the processing module is higher than a first power consumption fluctuation threshold value according to the first historical state information, determining that the processing module is in a fourth state;
and when the processing module is determined to be in a state other than the first state to the fourth state according to the first historical state information, determining that the processing module is in a fifth state.
6. The method of claim 5, wherein said determining a power control parameter of the processing module based on the operating state comprises:
determining a first power control parameter of the processing module when the processing module is in the first state, the second state, or the third state;
and when the processing module is in the fourth state or the fifth state, determining a second power control parameter of the processing module, wherein the power consumption of the processing module working with the second power control parameter is larger than the power consumption of the processing module working with the first power control parameter.
7. The method of claim 1, wherein the power control parameter comprises at least one of:
a first power consumption parameter indicating a fluctuation range of an average power consumption of the processing module;
a second power consumption parameter for indicating a maximum instantaneous power consumption value of the processing module.
8. The method of claim 1, wherein the method further comprises:
determining whether the electronic device is in a power saving mode;
the acquiring of the first historical state information of the processing module includes:
and when the power consumption saving mode is in, acquiring the first historical state information of the processing module.
9. An electronic device, comprising:
the acquisition module is used for acquiring first historical state information and second historical state information of the processing module; the first historical state information is the state information of the processing module before the current moment; the second historical state information is acquired before the first historical state information;
the third determining module is used for determining a condition parameter according to the second historical state information; the condition parameters are related to the working environment of the electronic equipment, the use habits of a user and the self configuration of the electronic equipment;
the first determining module is used for determining the working state of the processing module according to the first historical state information and the condition parameters;
the second determining module is used for determining the power control parameter of the processing module according to the working state;
and the control module is used for controlling the power consumption of the processing module according to the power control parameter.
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| CN112148095B (en) * | 2020-08-12 | 2022-06-21 | 深圳微步信息股份有限公司 | Control method for automatically loading heat dissipation parameters and mainboard system |
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