阅读说明：本技术 信息处理方法及电子设备 (Information processing method and electronic equipment ) 是由 张伟 于 2019-09-16 设计创作，主要内容包括：本申请实施例公开了一种信息处理方法及电子设备。所述信息处理方法,可包括：获取处理模组的第一历史状态信息；根据所述第一历史状态信息,确定所述处理模组的工作状态；根据所述工作状态,确定所述处理模组的功率控制参数；根据所述功率控制参数,控制所述处理模组的功耗。(The embodiment of the application discloses information processing methods and electronic equipment.)

1, an information processing method, comprising:

th historical state information of the processing module is obtained;

determining the working state of the processing module according to the th 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.

2. The method of claim 1, wherein the method further comprises:

determining the condition parameter of the working state according to second historical state information, wherein the second historical state information comprises th historical state information, or the second historical state information is acquired before th historical state information.

3. The method of claim 2, 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;

alternatively, the first and second electrodes may be,

and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.

4. The method of any of claim 1-3,

the th historical state information of the acquisition processing module comprises at least :

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.

5. A method according to claim 2 or 3, wherein the condition parameters include at least :

a frequency threshold;

a frequency fluctuation threshold;

a power consumption threshold;

a power fluctuation threshold.

6. The method of any of claims 1-3,

determining the working state of the processing module according to the th historical state information, wherein the working state comprises :

when the frequency of the processing module is determined to be lower than a frequency threshold value and the power consumption of the processing module is determined to be lower than a power consumption threshold value according to the historical state information, determining that the processing module is in a state;

when the frequency of the processing module is determined to be higher than a th frequency threshold and lower than a second frequency threshold according to the th historical state information, and the power consumption of the processing module is determined to be higher than a th 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 a th frequency 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 th 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;

when the fact that the frequency fluctuation value of a processing module in the electronic equipment is higher than a frequency variance threshold value and the power consumption fluctuation value of the processing module is higher than a power consumption fluctuation threshold value is determined according to the historical state information, the processing module is determined to be in a fourth state;

and when the processing module is determined to be in a state from the th state to the state beyond the fourth state according to the th historical state information, determining that the processing module is in a fifth state.

7. The method of claim 6, wherein said determining a power control parameter of said processing module based on said operating state comprises:

determining a th power control parameter for the processing module when the processing module is in the th 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 the processing module works with the second power control parameter is larger than the power consumption of the processing module when the processing module works with the th power control parameter.

8. The method of claim 1 or 2, wherein the power control parameter comprises at least :

th power consumption parameter, which is used to indicate 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.

9. The method according to claim 1 or 2, wherein the method further comprises:

determining whether the electronic device is in a power saving mode;

the th history state information of the acquisition processing module comprises:

when in the power saving mode, th history state information of the processing module is obtained.

10, an electronic device, comprising:

the acquisition module is used for acquiring th historical state information of the processing module;

an determining module, configured to determine an operating state of the processing module according to the th 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.

Technical Field

The present invention relates to the field of information technologies, and in particular, to information processing methods and electronic devices.

Background

Electronic devices (e.g., notebook computers) and the like include a Central Processing Unit (CPU), which is one of the main components of the electronic devices that consume electric energy.

Mode improving performance of the CPU or reducing Power consumption of the CPU 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 case of the mode , only sets of fixed TDP parameters are available, so that 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 minimization of the power consumption of the CPU cannot be realized in most cases.

Disclosure of Invention

In view of the above, it is desirable to provide information processing methods and electronic devices according to embodiments of the present invention.

The technical scheme of the invention is realized as follows:

an th aspect of the present embodiment provides information processing methods, including:

th historical state information of the processing module is obtained;

determining the working state of the processing module according to the th 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:

determining the condition parameter of the working state according to second historical state information, wherein the second historical state information comprises th historical state information, or the second historical state information is acquired before th 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;

alternatively, the first and second electrodes may be,

and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.

Based on the above scheme, the th history status information of the acquiring processing module includes at least :

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 parameters include at least :

a frequency threshold;

a frequency fluctuation threshold;

a power consumption threshold;

a power fluctuation threshold.

Based on the scheme, the working state of the processing module is determined according to the th historical state information, and the working state comprises :

when the frequency of the processing module is determined to be lower than a frequency threshold value and the power consumption of the processing module is determined to be lower than a power consumption threshold value according to the historical state information, determining that the processing module is in a state;

when the frequency of the processing module is determined to be higher than a th frequency threshold and lower than a second frequency threshold according to the th historical state information, and the power consumption of the processing module is determined to be higher than a th 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 a th frequency 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 th 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;

when the fact that the frequency fluctuation value of a processing module in the electronic equipment is higher than a frequency variance threshold value and the power consumption fluctuation value of the processing module is higher than a power consumption fluctuation threshold value is determined according to the historical state information, the processing module is determined to be in a fourth state;

and when the processing module is determined to be in a state from the th state to the state beyond the fourth state according to the th 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 th power control parameter for the processing module when the processing module is in the th 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 the processing module works with the second power control parameter is larger than the power consumption of the processing module when the processing module works with the th power control parameter.

Based on the above scheme, the power control parameters include at least :

th power consumption parameter, which is used to indicate 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 th history state information of the acquisition processing module comprises:

when in the power saving mode, th history state information of the processing module is obtained.

A second aspect of the embodiments of the present application provides electronic devices, including:

the acquisition module is used for acquiring th historical state information of the processing module;

an determining module, configured to determine an operating state of the processing module according to the th 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 equipment provided by the embodiment of the invention, th historical state information of the processing module is dynamically acquired, then the working state of the processing module is determined according to th historical state information, the power control parameter of the processing module is determined based on the working state, and finally the processing module is functioned based on the power control parameter, so that the power control on the processing module can be realized.

Drawings

Fig. 1 is a schematic flowchart of an 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 electronic devices according to an embodiment of the present application;

fig. 5 is a flowchart illustrating a fourth information processing method according to an embodiment of the present application.

Detailed Description

The invention will be described in further detail in with reference to the drawings and specific examples.

As shown in fig. 1, the present embodiment provides information processing methods, including:

s110, acquiring th history state information of the processing module;

s120, determining the working state of the processing module according to the historical state information of the th;

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 including but not limited to a notebook computer, a desktop computer, a tablet computer, a notebook tablet computer , a wearable device and the like.

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).

th historical state information of the processing module can comprise an actual power consumption value of the processing module and the working frequency of the processing module.

The th historical state information may be state information of processing modules prior to the current time.

In the embodiment of the present application, th historical state information is performed to determine the operating state of the processing module.

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 of:

a -th class power control parameter operable to control an average power of the processing module over a predetermined time period;

and the second type of power control parameter can be used for controlling the instantaneous power of the processing module within a preset time period.

In cases, the class power control parameters are used to define power ranges, which may include maximum power and minimum power.

The second type of power control parameter is instantaneous powers, which may be greater than their average power, so in cases, the second type of power control parameter may be greater than the upper limit of the 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 working state of the current 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 the embodiment of the present application, the operating state of the processing module is dynamically determined, for example, th historical state parameters of the processing module are collected in real time, in S120, the operating state of the processing module can be judged in real time based on the th historical power consumption parameters, in for example, th historical state parameters of the processing module are collected in real time, and then times of judgment of the operating state of the processing module is performed based on the th historical state parameters in time periods.

The power consumption actually obtained by the processing module may adversely affect the frequency of the processing module, e.g., the processing module may perform a down-conversion process when the actual power consumption obtained by the processing module is insufficient to support the high frequency operation of the processing module, and the frequency of the processing module may be related to the actual power consumption of the processing module, e.g., the higher the operating frequency of the processing module, such as , the higher the actual power consumption of the processing module.

In the embodiment of the application, the working state of the processing module is determined according to th historical state information before the current time of the processing module, then a power control parameter is given according to the working state to control the power of the processing module, in the aspect, the power consumption requirement of most parts of the processing module can be met, in the second aspect, the power waste caused by multiple power sources can be reduced, in the third aspect, the processing module can realize self resource configuration according to the actually obtained power through power control, and therefore the resource optimization configuration of the processing module in working is realized, in the fourth aspect, compared with a scheme of collecting and recording user habits, th historical state information of the processing module is directly collected and recorded, the type and the number of information needing to be collected are reduced, the collected and recorded data quantity and the information processing quantity for determining the working state are reduced, and therefore, the operation of electronic equipment is simplified, and excessive additional load caused by the division of the processing module due to the self working state is reduced.

In , the determination of the operation status of the processing module according to the th historical status information in S120 uses the determination condition for determining the operation status of the processing module.

In , the condition parameters involved in determining the conditions are determined dynamically.

In embodiments, as shown in fig. 2, the method further comprises:

and S100, determining the condition parameters of the working state according to second historical state information, wherein the second historical state information comprises th historical state information, or the second historical state information is acquired before th historical state information.

Thus, the step S120 may include determining an operating status of the processing module according to the condition parameter and the th historical status information.

In the embodiment of the present application, the second historical state information is also an acquired parameter for acquiring an actual state of the processing module.

In example embodiments, the second historical state information may include the th historical state information, e.g., the second historical state information is equal to the th historical state parameter, or the second historical state information includes the th historical state information and state information prior to the th historical state information.

In still other embodiments, the second historical state information may include previous historical state information to th historical state information, at which time the second historical state information does not include the th historical state information.

Assuming that the operating state of the processing module is determined times every N seconds, the condition parameter is determined times every M seconds, if M is greater than X times 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 th historical state information.

In , the operation status of the processing module is updated according to a th cycle, and the condition parameter is updated according to a second cycle, wherein the second cycle is greater than or equal to the th cycle.

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 parameter can be related to the working environment of the electronic device, the use habit of the user and the self-configuration of the device, and can be adapted to the self-condition of the electronic device.

The working environment includes, but is not limited to, at least one of working temperature, working noise, and working brightness.

The user usage habits include: the time length of the electronic equipment used by the user, the application type preferred by the user, the specific application preferred by the user and the function of the electronic equipment preferred by the user.

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 , 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;

alternatively, the first and second electrodes may be,

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 , the second historical state information is analyzed using an inductive learning algorithm in a machine learning algorithm to obtain the condition parameter.

In , the second historical state information is learned using a deep learning algorithm, including but not limited to a neural network, to also determine the condition parameters for the P operating states.

In embodiments, the S110 can include at least 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.

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 , the historical power consumption fluctuation value may be a power consumption variance value reflecting the historical power consumption fluctuation obtained by performing variance calculation according to the collected historical power consumption value.

In still other embodiments, the historical power consumption fluctuation value may also be based on a difference between a minimum actual power consumption value and a maximum power consumption value over time periods.

In 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 device, updating the condition parameter corresponding to the user identity information according to the second historical state information of the processing module during operation, so that when the user corresponding to the user identity information again uses the electronic device, times, the power control parameter of the processing module in the electronic device is determined, and the power of the processing module is controlled.

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.

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.

Thus, even if the electronic device is public devices, the condition parameters may be different when determining the operating state of the processing module based on the identification of the user identification information, so that the determination of the operating state of the processing module can be adapted to the current status of the electronic device, ensuring the optimization of the power control of the processing module.

In , the condition parameters include at least :

a frequency threshold;

a frequency fluctuation threshold;

a power consumption threshold;

a power fluctuation threshold.

In embodiments, the S120 may include of:

when the frequency of the processing module is determined to be lower than a frequency threshold value and the power consumption of the processing module is determined to be lower than a power consumption threshold value according to the historical state information, determining that the processing module is in a state;

when the frequency of the processing module is determined to be higher than a th frequency threshold and lower than a second frequency threshold according to the th historical state information, and the power consumption of the processing module is determined to be higher than a th 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 a th frequency 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 th 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;

when the fact that the frequency fluctuation value of a processing module in the electronic equipment is higher than a frequency variance threshold value and the power consumption fluctuation value of the processing module is higher than a power consumption fluctuation threshold value is determined according to the historical state information, the processing module is determined to be in a fourth state;

and when the processing module is determined to be in a state from the th state to the state beyond the fourth state according to the th historical state information, determining that the processing module is in a fifth state.

In the embodiment of the present application, the working states of the processing module are defined as 5 types, and these 5 types of states can more comprehensively cover various application scenarios of the processing module.

In , the S130 may include:

determining a th power control parameter for the processing module when the processing module is in the th 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 the processing module works with the second power control parameter is larger than the power consumption of the processing module when the processing module works with the th power control parameter.

In embodiments, the power control parameters include at least :

th power consumption parameter, which is used to indicate 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.

In , after determining the power control parameter, power is provided to the processing module based on the power control parameter to achieve power control of the processing module.

In 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 electronic devices, including:

an obtaining module 110, configured to obtain th history status information of the processing module;

the determining module 120 is used for determining the working state of the processing module according to the 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 , the obtaining module 110, the determining module 120, the second determining module 130, and the control module 140 may be program modules that, when executed by a processor, are capable of obtaining the th historical state information, determining the operating state, determining the power control parameter, and controlling the power consumption of the processing module.

In still other embodiments, the acquisition module 110, the determination module 120, the second determination module 130, and the control module 140 may be a hard-soft combination module including, but not limited to, a programmable array including, but not limited to, a complex programmable array and a field programmable array.

In embodiments, the apparatus further comprises:

a third determining module, configured to determine a condition parameter of the operating state according to second historical state information, where the second historical state information includes the th historical state information, or the second historical state information is obtained before the th historical state information.

In , the third determining module is specifically configured to perform as follows:

learning the second historical state information based on a machine learning algorithm to obtain the condition parameters;

alternatively, the first and second electrodes may be,

and learning the second historical state information based on a deep learning algorithm to obtain the condition parameters.

In , the obtaining module 110110 is specifically configured to execute at least :

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.

In , the condition parameters include at least :

a frequency threshold;

a frequency fluctuation threshold;

a power consumption threshold;

a power fluctuation threshold.

In , the determining module 120 is specifically configured to perform of:

when the frequency of the processing module is determined to be lower than a frequency threshold value and the power consumption of the processing module is determined to be lower than a power consumption threshold value according to the historical state information, determining that the processing module is in a state;

when the frequency of the processing module is determined to be higher than a th frequency threshold and lower than a second frequency threshold according to the th historical state information, and the power consumption of the processing module is determined to be higher than a th 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 a th frequency 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 th 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;

when the fact that the frequency fluctuation value of a processing module in the electronic equipment is higher than a frequency variance threshold value and the power consumption fluctuation value of the processing module is higher than a power consumption fluctuation threshold value is determined according to the historical state information, the processing module is determined to be in a fourth state;

and when the processing module is determined to be in a state from the th state to the state beyond the fourth state according to the th historical state information, determining that the processing module is in a fifth state.

In , the second determining module 130 is specifically configured to perform as follows:

determining a th power control parameter for the processing module when the processing module is in the th 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 the processing module works with the second power control parameter is larger than the power consumption of the processing module when the processing module works with the th power control parameter.

In embodiments, the power control parameters include at least :

th power consumption parameter, which is used to indicate 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.

In embodiments, the apparatus further includes a third determining module to determine whether the electronic device is in a power saving mode;

the obtaining module 110 is specifically configured to obtain th history 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 th state, a second state, a third state, a fourth state and a fifth state, the th state may also be referred to as an idle state, the second state may be a light load state, which may also be referred to as a battery life state (battery life), the third state may be a heavy load continuous state, which may also be referred to as a sustain state (sustain), the fourth state may be a heavy load burst state, which may also be referred to as a (burst), the fifth state may be other states than the th state to the fourth state, the fifth state may also be referred to as a semi-active state (semi active), and the 5 states may cover all possible operating states of the CPU, that is, the CPU states when all the APPs run.

For the 5 states, the (DPTF) parameters of the CPU aiming at the 5 scenes can be debugged, so that the running performance of the CPU is provided, and unnecessary power consumption of the CPU is reduced at the same time.

According to the technical scheme provided by the example, the intelligent optimization covers the scene , the workload of a research and development stage is reduced, and a machine learning algorithm is scalable, so that the goal of automatically learning the behavior habits of the user is achieved.

Example 2:

as shown in fig. 5, the present example provides information processing methods, 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 conditional 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 th state/second state (battery life state/idle state), third state (heavy load maintenance state), fourth state (heavy load burst state), and fifth state (semi-active state), respectively.

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 use sets of DPTF parameters, these sets of DPTF parameters are stored in DPTF file 1, including Power Limit max to (Power Limit 1max, PL1max), (Power Limit 1min, PL1max), and (Power Limit2, PL2), respectively, PL1max ═ PL1min ═ 5W, and PL2 ═ 12W, located in DPTF file 1 as shown in fig. 5.

The latter two states may share sets of DPTF parameters, these sets of DPTF parameters are stored in DPTF file 2, including PL1max, PL1min, and PL2, respectively, PL1max ═ PL1min ═ 8W, and PL2 ═ 25W, located in DPTF file 2 as shown in fig. 5.

The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units into only logical functional divisions, and other divisions may be possible in actual practice, e.g., multiple units or components may be combined, or may be integrated into another systems, or features may be omitted or not executed.

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, that is, may be located in places, may also be distributed on multiple network units, and some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.

In addition, all the functional units in the embodiments of the present invention may be integrated into processing modules, each unit may be units individually, or two or more units may be integrated into units, and the integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

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.

It will be understood by those skilled in the art that all or part of the steps of implementing the above method embodiments may be implemented by hardware associated with program instructions, and that the program may be stored in computer readable storage medium, and when executed, the program performs the steps of the above method embodiments, and the storage medium includes various media capable of storing program codes, such as removable storage device, Read-Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disk.

The above description is only a specific embodiment 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 conceive of changes or substitutions within the technical scope of the present example disclosure, and all the changes or substitutions 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.