CN112486683B - Processor control method, control device, and computer-readable storage medium - Google Patents

Abstract

The present application discloses a processor control method, a control device, and a computer-readable storage medium. The method includes: determining the predicted strength value of at least one processor in the distributed storage cluster at the current moment; determining the processing according to the predicted strength value the operating parameters of the processor; adjust the operating parameters according to the operating conditions of the processor, and control the processor to operate according to the adjusted operating parameters, so as to reduce the energy consumption consumed by the processor when performing tasks. The present invention solves the technical problem that the actual running requirements of the processors when executing tasks cannot be met when controlling the operation of the cluster based on the results calculated by the energy consumption model, and achieves the reduction of the energy consumption consumed by the processors when executing tasks.

Description

Processor control method, control device, and computer-readable storage medium

technical field

The present application relates to the field of computer technology, and in particular to a processor control method, a control device, and a computer-readable storage medium.

Background technique

With the rapid development of the Internet, a large amount of data is generated exponentially. Among them, the distributed file system can be used to store and process a large amount of data, the most representative of which is HDFS, which can reliably store large data files and stream data with high bandwidth.

In prior art, the method for reducing HDFS energy consumption mainly contains: the first, change CPU utilization rate and frequency, establish corresponding energy consumption model such as establishing the relation between computer power and CPU utilization rate and frequency, according to different tasks The energy consumption of the system needs to be adjusted; second, a predictive model is established, and predictive control designs system performance optimization indicators based on control objectives, so that the performance indicators in the future prediction time domain can be optimized; third, through GreenHDFS, GreenHDFS logically converts data Servers in the center are organized in multiple dynamically provisioned hot and cold zones, each with unique performance, cost, and power characteristics, and each zone is placed by power and data best suited to the class of data in that zone Policy management that avoids starting servers in cold zones and maximizes the use of existing powered-on servers in its server allocation decisions to maximize energy savings.

At present, some mainstream CPUs cannot adjust the frequency, and most of them can switch cores, but there are few studies on switching CPU cores to reduce energy consumption during HDFS work. And most of the methods to reduce HDFS energy consumption are carried out by establishing energy consumption models, ignoring the research on engineering implementation. For large-scale clusters in the working state, it is unrealistic to directly regulate by establishing an energy consumption model, and the anti-interference ability of the implementation of regulation is weak, and the actual demand cannot be met when the cluster is controlled according to the calculation results of the energy consumption model.

Contents of the invention

The embodiments of the present application provide a processor control method, a control device, and a computer-readable storage medium, aiming to solve the problem that the actual operation requirements of the processor when executing tasks cannot be met when controlling the operation of the cluster based on the results calculated by the energy consumption model. .

To achieve the above object, the present application provides a processor control method on the one hand, including:

determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment;

determining an operating parameter of the processor based on the predicted intensity value;

The operating parameters are adjusted according to the operating conditions of the processor, and the processor is controlled to operate according to the adjusted operating parameters, so as to reduce energy consumption when the processor executes tasks.

Optionally, the step of adjusting the operating parameters according to the operating conditions of the processor includes:

Acquiring the actual intensity value of the processor within the first preset duration;

determining the maximum operating parameter corresponding to the actual intensity value;

When the processor operates according to the maximum parameter within the first preset time period, counting the time threshold for the processor to operate according to the maximum operating parameter;

When the time threshold is greater than a first preset time threshold, the processor is controlled to increase the current operating parameter.

Optionally, after the step of obtaining the actual intensity value of the processor within the first preset duration, the method includes:

determining the minimum operating parameter corresponding to the actual intensity value;

When the processor operates according to the minimum parameter within the first preset time period, counting the time threshold for the processor to operate according to the minimum operation parameter;

When the time threshold is greater than a second preset time threshold, the processor is controlled to reduce the current operating parameter.

Optionally, the step of determining the current prediction strength value of at least one processor in the distributed storage cluster includes:

Get the current system time of the processor;

Determine the historical intensity value corresponding to the system time as the predicted intensity value at the current moment.

Optionally, the step of determining the current prediction strength value of at least one processor in the distributed storage cluster includes:

acquiring each of the historical intensity values of the processor in a first preset time period;

A data model is established for the historical intensity value, and the predicted intensity value is obtained through the data model.

Optionally, the step of obtaining the actual intensity value of the processor for each running time period includes:

Obtain the number of times the processor reads data and writes data during the running time period;

The actual intensity value is determined according to the times of reading data and writing data.

Optionally, the step of determining the operating parameters of the processor according to the predicted intensity value includes:

determining a band function corresponding to the predicted intensity value;

The operating parameter corresponding to the band function is determined as the operating parameter of the processor.

Optionally, the step of determining the band function corresponding to the predicted intensity value includes:

Comparing the predicted intensity value with the historical intensity value, and confirming that the band function corresponding to the historical intensity value pair that is consistent with the comparison is the band function of the predicted intensity value.

In addition, in order to achieve the above object, another aspect of the present application provides a processor control system, the control system includes a processor, a memory, and a processor control program stored in the memory and operable on the processor, the processor control program When executed by the processor, the steps of the above method controlled by the processor are realized.

In addition, in order to achieve the above object, another aspect of the present application also provides a computer-readable storage medium, on which a processor control program is stored, and when the processor control program is executed by the processor, the above processor-controlled method steps.

In this application, by determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment, and then determining the operating parameters of the processor according to the predicted intensity value, the operating conditions of the processor are obtained, and according to the processor Adjust the operating parameters according to the operating conditions of the processor, control the processor to operate according to the adjusted operating parameters, so as to reduce the energy consumption of the processor when performing tasks, and at the same time adjust the operating parameters according to the actual operating conditions of the processor, and also It avoids the problem of stuck processing due to the fact that the operating parameter obtained according to the predicted intensity value is smaller than the operating parameter required by the processor to execute the task at the current moment.

Description of drawings

FIG. 1 is a schematic diagram of the terminal structure of the hardware operating environment involved in the solution of the embodiment of the present application;

FIG. 2 is a schematic flowchart of an embodiment of a processor control method of the present application;

FIG. 3 is a schematic flowchart of another embodiment of a processor control method of the present application.

The realization, functional features and advantages of the present application will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

The main solution of the embodiment of the present application is to: determine the predicted strength value of at least one processor in the distributed storage cluster at the current moment; determine the operating parameters of the processor according to the predicted strength value; The operating parameters are adjusted, and the processor is controlled to run according to the adjusted operating parameters, so as to reduce the energy consumption when the processor executes tasks.

In the prior art, the energy consumption generated by the distributed storage cluster is adjusted by establishing a predictive model to control each processor in the distributed storage cluster to operate according to the predicted operating parameters when performing tasks at various stages. However, when the operating parameters obtained by prediction are used to control the operation of the processor, the difference between the actual intensity value and the predicted intensity value of the processor in the actual operation process is not taken into account, resulting in the processor running according to the operating parameters obtained by the prediction model. , there is a problem that the operating parameters are set too large or too small, resulting in the processor being unable to meet the data operation requirements during operation or causing waste of power consumption when the operating parameters are set too large.

As shown in FIG. 1 , FIG. 1 is a schematic diagram of a terminal structure of a hardware operating environment involved in the solution of the embodiment of the present application.

As shown in FIG. 1 , the terminal may include: a processor 1001 , such as a CPU, a network interface 1004 , a user interface 1003 , a memory 1005 , and a communication bus 1002 . Wherein, the communication bus 1002 is used to realize connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. Optionally, the network interface 1004 may include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 can be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001 .

Optionally, the terminal may further include a camera, an RF (Radio Frequency, radio frequency) circuit, a sensor, a remote controller, an audio circuit, a WiFi module, a detector, and the like. Of course, the terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, and a temperature sensor, which will not be repeated here.

Those skilled in the art can understand that the terminal structure shown in FIG. 1 does not constitute a limitation on the terminal device, and may include more or less components than those shown in the figure, or combine some components, or arrange different components.

As shown in FIG. 1 , the memory 1005 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module, and a processor control program.

In the terminal shown in Figure 1, the network interface 1004 is mainly used to connect to the background server and perform data communication with the background server; the user interface 1003 is mainly used to connect to the client (client) and perform data communication with the client; and the processor 1001 can be used to call the processor control program stored in memory 1005, and perform the following operations:

determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment;

determining an operating parameter of the processor based on the predicted intensity value;

The operating parameters are adjusted according to the operating conditions of the processor, and the processor is controlled to operate according to the adjusted operating parameters, so as to reduce energy consumption when the processor executes tasks.

Referring to FIG. 2 , FIG. 2 is a schematic flowchart of an embodiment of a processor control method of the present application.

The embodiment of the present application provides an embodiment of the processor control method. It should be noted that although the logic sequence is shown in the flowchart, in some cases, the sequence shown or described steps.

Processor control methods include:

Step S10, determining the predicted strength value of at least one processor in the distributed storage cluster at the current moment;

A distributed storage cluster is to build a network topology through multiple storage servers to form a storage server cluster. In the storage server cluster, relevant algorithms can be used for data reading and writing operations, that is, multiple processors share the processing data. When there is a large amount of data that needs to be analyzed and processed, it solves the problem of excessive storage load.

In practical application, each processing in the server cluster is independent of each other and processes different data. Therefore, by calculating the strength values of different processors at different times, the operating parameters of the processors included in the distributed storage cluster can be managed, so that the operation of each processor can meet the current task requirements.

In this embodiment, the predicted intensity value is the intensity value predicted by the processor at the current moment. Specifically, in this embodiment, the method for obtaining the predicted strength value may be obtained by obtaining the historical strength value of each processor.

The step of determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment includes:

Step S11, obtaining the current system time of the processor;

Step S12, determining the historical intensity value corresponding to the system time as the predicted intensity value at the current moment.

The historical intensity value is an actual running intensity value of the processor when executing a task. In this embodiment, by obtaining the intensity values of the actual operation of the processor at different times as the historical intensity values, and recording the time period for obtaining each intensity value when the processor executes tasks, by analyzing the specific time period in which the system time belongs to the recorded time period time period, and then obtain the historical strength of this time period as the predicted strength at the current moment.

Optionally, in this embodiment, the preset time range can also be divided into multiple time periods, and the historical strength value of the actual operation of the processor at each time is obtained, and then when the predicted strength value of the processor at the current moment is obtained , determine the time period of the system time at the current moment, and then obtain the historical intensity value of this period, and use the historical intensity value as the predicted intensity value. Specifically, take time as the cycle (24h), divide 24 hours into different time periods on average (set a time period for each hour), and then obtain the actual running intensity value (historical intensity value) of each processor in different time periods . On the second day, the 24 hours are likewise divided into time periods equal to the length of each time period on the previous day. When obtaining the current predicted strength value of the processor, the time period in which the current system time is determined is determined by obtaining the current system time, and the strength value corresponding to the time period is further determined to be the predicted strength value at the current moment.

In this embodiment, by obtaining the system time during the actual operation of the processor, the time period of the system time is determined, and then the historical intensity value of the system in the time period is obtained, and the historical intensity value of the current system is determined to be For the predicted strength value of time, the historical strength value corresponding to the time period to which the current moment belongs is determined as the predicted strength value of the processor, which improves the accuracy of the predicted strength value.

The step of determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment includes:

Step S111, obtaining each of the historical intensity values of the processor in the first preset time period;

Step S112, establishing a data model according to the historical intensity value to obtain the predicted intensity value.

In this embodiment, the first preset duration can be set to one week, that is, the historical strength value of each processor in the previous week is obtained as the data for obtaining the predicted strength value of the next week, and the first preset duration The setting may be determined according to the situation of using the processor for data processing, specifically, the first preset duration may also be set to one month. Wherein, the historical intensity values in the first preset time period may include multiple ones, specifically, the historical intensity values of different time periods are acquired periodically at intervals of one hour, and the historical intensity values and time periods are mapped and stored. For example, from 00:00 to 01:00, the historical intensity values from Monday to Sunday are x1, x2, x3...x7 respectively, and the historical intensity values corresponding to 168 time periods in a week are respectively obtained, and the historical intensity values and each time The segment is an independent variable, which is brought into the data model (SARIMA model) for data analysis, and then the predicted intensity values corresponding to each time segment in the next 24 hours are obtained.

The step of acquiring each of the historical intensity values of the processor in the first preset time period includes:

Step S1111, obtaining the number of times the processor reads data and writes data within each time period of the first preset time period;

Step S1112, determining the historical intensity value according to the times of reading data and writing data.

To analyze and store logs on the datanode, you can use the method of collecting the number of reads and writes in each time period of the first preset duration. Let the sampling time be, the number of reads is a _i , the number of writes is b _i , and the history intensity is set is D _i , then

Among them, θ _i and γ _i are the corresponding coefficients when different processors read and write data. For example, the coefficient of reading data corresponding to processor 1 is θ ₁ , and the coefficient of writing data is γ ₁ . They will read The number of writes is converted into a historical intensity value D _i representing the processor's processing tasks in each time period. A predicted intensity value is then determined based on the plurality of historical intensity values and each corresponding time period. In this embodiment, by obtaining the historical strength value of the processor in multiple time periods of the first preset duration, and then determining the predicted strength value of the processor at the current moment, the predicted current strength value is determined according to the historical strength value by means of data analysis. The predicted strength value at the moment improves the accuracy of obtaining the predicted strength value at the current moment.

Step S20, determining the operating parameters of the processor according to the predicted intensity value;

The operating parameters of the processor are the number of cores and the operating frequency of the processor executing the task at the current moment.

Specifically, in this application, the operating frequency of the processor includes two gears of powersave and performance. The number of cores of the processor is 1 to 8. When the operating frequency of different gears and the number of cores are combined to perform tasks, the power of the processor There are differences, and their intensity values also vary. In this application, using the different power corresponding to the intensity value of the processor, and the power difference when the processor performs tasks in combination with different operating frequencies and core numbers, the correspondence between the intensity value and the operating frequency and the number of cores is established Then, by obtaining the corresponding relationship between the operating frequency and the number of cores corresponding to the intensity value consistent with the predicted parameter value, the operating parameters of the processor at the current moment can be determined through the predicted intensity value.

Step S30 , adjusting the operating parameters according to the operating conditions of the processor, and controlling the processor to operate according to the adjusted operating parameters, so as to reduce the energy consumed by the processor when performing tasks.

It can be understood that, in the process of actual use, since there is a difference between the intensity of the executed task and the predicted intensity predicted according to the historical parameters, the operating parameters can be adjusted according to the operating conditions of the current processor, and the control processor can be controlled according to the adjusted run with the operating parameters of the processor, so that the operating parameters of the processor match the operating parameters required to execute the task at the current moment.

In this application, by determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment, and then determining the operating parameters of the processor according to the predicted intensity value, the operating conditions of the processor are obtained, and according to the processor Adjust the operating parameters according to the operating conditions of the processor, control the processor to operate according to the adjusted operating parameters, so as to reduce the energy consumption of the processor when performing tasks, and at the same time adjust the operating parameters according to the actual operating conditions of the processor, and also It avoids the problem of stuck processing due to the fact that the operating parameter obtained according to the predicted intensity value is smaller than the operating parameter required by the processor to execute the task at the current moment.

Based on the above embodiment, another embodiment of the present application is proposed. The step of adjusting the operating parameters according to the operating conditions of the processor includes:

Step S41, acquiring the actual intensity value of the processor within the first preset duration;

Step S42, determining the maximum operating parameter corresponding to the actual intensity value;

Step S43, when the processor operates according to the maximum parameter within the first preset time period, counting the time threshold for the processor to operate according to the maximum operating parameter;

Step S44, when the time threshold is greater than a first preset time threshold, control the processor to increase the current operating parameter.

The actual intensity value can be obtained through the installed measuring equipment—smart meter. Specifically, the smart meter can establish a wired connection with the processor, and different connection interfaces represent different connected processors. When obtaining the actual intensity value, the actual intensity value fed back in the smart meter is obtained by designing a script program corresponding to the processor. The first preset duration is the duration from the system time when the current processor starts counting to the system time at the current moment when the current processor is executing the task. When the current time is 12:00, the system time when the counting starts is 11:00 , it means that the first preset duration is 1 hour. Count the actual intensity value of the processor during this hour, and further determine the maximum operating parameter of the processor according to the actual intensity value. When the processor runs according to the maximum operating parameter for a period longer than the first preset time threshold (30 minutes), Confirm that the operating parameters obtained by the processor according to the predicted intensity value are smaller than the operating parameters of the processor when executing tasks, then increase the operating parameters, for example, if the number of cores is 4, the gear of the operating frequency is powersave, and the number of cores is adjusted to 5. The operating frequency is powersave. In this way, when the processor runs according to the adjusted operating parameters, it can smoothly execute processing tasks.

After the step of obtaining the actual intensity value of the processor within the first preset duration, it includes:

Step S45, determining the minimum operating parameter corresponding to the actual intensity value;

Step S46, when the processor operates according to the minimum parameter within the first preset time period, counting the time threshold for the processor to operate according to the minimum operation parameter;

Step S47, when the time threshold is greater than a second preset time threshold, control the processor to reduce the current operating parameter.

Further, if the first preset duration is one hour, the actual intensity value of the processor during this hour is counted, and the minimum operating parameter of the processor is determined according to the actual intensity value. When the processor operates according to the minimum operating parameter When it is greater than the second preset time threshold (20 minutes), confirm that the operating parameter obtained by the processor according to the predicted intensity value is greater than the operating parameter of the processor when executing the task, then reduce the operating parameter, for example, from the number of cores to 4, run The gear of the frequency is power save, the number of cores is adjusted to 3, and the operating frequency is power save. In this way, the energy consumption of the processor when performing tasks is reduced.

Referring to FIG. 3 , FIG. 3 is another embodiment of the present application. The step of determining the operating parameters of the processor according to the predicted intensity value includes:

Step S21, determining the band function corresponding to the predicted intensity value;

Step S22, determining the operating parameter corresponding to the band function as the operating parameter of the processor.

The band function is a piecewise function corresponding between the historical intensity value and the power of the processor. It can be understood that in practical applications, there is a many-to-one relationship between the intensity value and the power of the processor, and the historical There is also a many-to-one relationship between the intensity value and the operating parameters of the processor. In this embodiment, by using the band function corresponding to the predicted intensity value, the operating parameter corresponding to the band function is determined as the operating parameter of the processor.

The step of determining the band function corresponding to the predicted intensity value includes:

Step S23, comparing the predicted intensity value with the historical intensity value, and confirming that the band function corresponding to the historical intensity value pair that is consistent with the comparison is the band function of the predicted intensity value.

It can be understood that in this embodiment, the obtained band function is determined according to the historical intensity value, so when obtaining the predicted intensity band function, it is necessary to compare the predicted intensity value with the historical intensity value, so as to obtain the predicted intensity value. The band function matching the intensity value, and then determine the operating power of the processor according to the value of the band function, and obtain the number of cores and operating frequency required for the processor to perform tasks, which improves the operating parameters of the processor when performing processing tasks The accuracy of control reduces energy consumption.

In addition, the present application also provides a processor control device, the processor control device includes a processor, a memory, and a processor control program stored in the memory and operable on the processor, the processor When the control program is executed by the processor, the steps of any one of the above processor control methods are implemented.

In addition, the present application also provides a computer-readable storage medium, where a processor control program is stored on the computer-readable storage medium, and when the processor control program is executed by the processor, any one of the above processor control methods can be implemented. step.

Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowcharts and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

It should be noted that, in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means can be embodied by one and the same item of hardware. The use of the words first, second, and third, etc. does not indicate any order. These words can be interpreted as names.

While alternative embodiments of the present application have been described, additional changes and modifications to these embodiments may be made by those skilled in the art once the basic inventive concept is appreciated. Therefore, it is intended that the appended claims be interpreted to cover alternative embodiments and all changes and modifications that fall within the scope of the application.

Obviously, those skilled in the art can make various changes and modifications to the application without departing from the spirit and scope of the application. In this way, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims (6)

1. A processor control method, characterized in that, the processor control method comprises: determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment; The step of determining the predicted intensity value of at least one processor in the distributed storage cluster at the current moment includes: Get the current system time of the processor; determining the historical intensity value corresponding to the system time as the predicted intensity value at the current moment; Determine the operating parameters of the processor according to the predicted intensity value, the operating parameters are the number of cores and the operating frequency of the processor executing the task at the current moment; Acquiring the actual intensity value of the processor within the first preset duration; The step of obtaining the actual intensity value of the processor for each running time period includes: Obtain the number of times the processor reads data and writes data during the running time period; determining the actual intensity value according to the number of times of reading data and writing data; determining the minimum operating parameter corresponding to the actual intensity value; When the processor operates according to the minimum operating parameter within the first preset time period, counting the time threshold for the processor operating according to the minimum operating parameter; When the time threshold is greater than a second preset time threshold, controlling the processor to reduce a current operating parameter; determining the maximum operating parameter corresponding to the actual intensity value; When the processor operates according to the maximum operating parameter within the first preset time period, counting the time threshold for the processor operating according to the maximum operating parameter; When the time threshold is greater than a first preset time threshold, controlling the processor to increase the current operating parameter; The processor is controlled to run according to the adjusted operating parameters, so as to reduce the energy consumed by the processor when performing tasks. 2. The processor control method according to claim 1, wherein the step of determining the predicted strength value of at least one processor in the distributed storage cluster at the current moment comprises: acquiring each of the historical intensity values of the processor in a first preset time period; A data model is established for the historical intensity value, and the predicted intensity value is obtained through the data model. 3. The processor control method according to claim 1, wherein the step of determining the operating parameters of the processor according to the predicted intensity value comprises: determining a band function corresponding to the predicted intensity value; The operating parameter corresponding to the band function is determined as the operating parameter of the processor. 4. The processor control method according to claim 3, wherein the step of determining the band function corresponding to the predicted intensity value comprises: Comparing the predicted intensity value with the historical intensity value, and confirming that the band function corresponding to the historical intensity value pair that is consistent with the comparison is the band function of the predicted intensity value. 5. A processor control device, characterized in that the processor control device comprises a processor, a memory, and a processor control program stored on the memory and operable on the processor, the processor When the control program is executed by the processor, the steps of the processor control method according to any one of claims 1-4 are implemented. 6. A computer-readable storage medium, characterized in that a processor control program is stored on the computer-readable storage medium, and when the processor control program is executed by a processor, any one of claims 1 to 4 is implemented. Steps in the item handler control method.

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