Computing power management method and system of computing power server based on data analysis

Abstract

The invention discloses a computing power management method and system of a computing power server based on data analysis, and relates to the technical field of computing power server management.The computing power management method comprises the steps that data extraction is conducted on a database system, and historical operation data of the computing power server is obtained; analyzing and processing the historical operation data of the computing power server to obtain computing power average distribution information of the computing power server; and analyzing and processing the computing power average distribution information of the computing power server, and determining a computing power overload time interval and a computing power excess time interval. The method comprises the following steps: analyzing historical operation data of the computing power server, determining a computing power overload time interval and a computing power excess time interval of the computing power server, analyzing the computing power required by tasks executed in the computing power overload time interval, and executing part of the tasks in the computing power excess time interval. The overload condition of the computing power server is avoided, the service life of the computing power server is prolonged, and meanwhile balanced use of the computing power server is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of computing power server management, and specifically relates to a computing power management method and system for a computing power server based on data analysis. Background Art

[0002] A computing power server is a server specifically used for performing high-performance computing and data processing tasks, with powerful computing capabilities and high-speed data processing capabilities. It is usually used for performing complex scientific calculations, data analysis, artificial intelligence training, and inference tasks.

[0003] The computing power server may execute different tasks at different times. However, when the computing power server executes multiple tasks in a certain period and fewer tasks in other periods, it will cause the computing power server to be overloaded with computing power in a certain period, reducing the service life of the computing power server. Summary of the Invention

[0004] To solve the above technical problems, a computing power management method and system for a computing power server based on data analysis are provided. The present technical solution solves the problem that the computing power server may execute different tasks at different times. However, when the computing power server executes multiple tasks in a certain period and fewer tasks in other periods, it will cause the computing power server to be overloaded with computing power in a certain period, reducing the service life of the computing power server as described in the above background art.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A computing power management method for a computing power server based on data analysis, including:

[0007] Based on a data analysis terminal, extract data from the database system to obtain the historical operation data of the computing power server;

[0008] Based on the data analysis terminal, analyze and process the historical operation data of the computing power server to obtain the computing power average distribution information of the computing power server;

[0009] Based on the data analysis terminal, analyze and process the computing power average distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval;

[0010] Based on the data analysis terminal, analyze and process the computing power overload time interval to determine the task reallocation;

[0011] The data analysis terminal analyzes and processes the computing power surplus time interval according to the task reallocation to determine the computing power management plan of the computing power server.

[0012] Preferably, the step of analyzing and processing the historical operation data of the computing power server by the data analysis terminal to obtain the average computing power distribution information of the computing power server specifically includes the following steps:

[0013] The data analysis terminal classifies the historical operation data of the computing power server by date to obtain the first historical operation data of the computing power server;

[0014] The data analysis terminal performs secondary classification processing on the first historical operation data of the computing power server by hour to obtain the second historical operation data of the computing power server;

[0015] Based on the data analysis terminal, analyze and process the second historical operation data of the computing power server to obtain several groups of computing power distribution information of the computing power server;

[0016] Based on the data analysis terminal, analyze and process several groups of computing power distribution information of the computing power server to obtain the average computing power distribution information of the computing power server.

[0017] Preferably, the step of analyzing and processing several groups of computing power distribution information of the computing power server by the data analysis terminal to obtain the average computing power distribution information of the computing power server specifically includes the following steps:

[0018] The data analysis terminal classifies the computing power analysis information of several groups of computing power servers by the same time to determine the computing power distribution information of the computing power server at the same time;

[0019] Based on the data analysis terminal, perform a summation calculation on the computing power distribution information of the computing power server at the same time to determine the total computing power usage data of the computing power server at the same time;

[0020] Based on the data analysis terminal, perform calculation processing on the total computing power usage data of the computing power server at the same time to obtain the average computing power distribution information of the computing power server;

[0021] Among them, the specific calculation formula for obtaining the average computing power distribution information of the computing power server is:

[0022]

[0023] In the formula, C1 is the average computing power distribution information of the computing power server; C i is the computing power usage data of the computing power server at the same time; n is the specific number of the computing power usage data of the computing power server at the same time.

[0024] Preferably, the step of analyzing and processing the average computing power distribution information of the computing power server by the data analysis terminal to determine the computing power overload time interval and the computing power surplus time interval specifically includes the following steps:

[0025] Based on the data analysis terminal, parameter calls are made to the computing power server to determine the model of the computing power server;

[0026] The data analysis terminal retrieves information from the database system according to the model of the computing power server to obtain the R & D documents of the computing power server;

[0027] Based on the data analysis terminal, data analysis and processing are performed on the R & D documents of the computing power server to determine the computing power call threshold, where the computing power call threshold includes a first computing power call threshold and a second computing power call threshold;

[0028] Based on the data analysis terminal, comparison and judgment processing are performed on the computing power call threshold and the computing power average distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval.

[0029] Preferably, the step of performing comparison and judgment processing on the computing power call threshold and the computing power average distribution information of the computing power server based on the data analysis terminal to determine the computing power overload time interval and the computing power surplus time interval specifically includes the following steps:

[0030] Based on the data analysis terminal, judgment processing is performed on the computing power call threshold and the computing power average distribution information of the computing power server;

[0031] If the computing power average distribution information of the computing power server is greater than or equal to the first computing power call threshold, the computing power call of the computing power server is excessive, and the data analysis terminal reads and processes the time information of the computing power average distribution information of the computing power server to determine the computing power overload time interval;

[0032] If the computing power average distribution information of the computing power server is less than the first computing power call threshold and the computing power average distribution information of the computing power server is greater than or equal to the second computing power call threshold, the computing power call of the computing power server is normal;

[0033] If the computing power average distribution information of the computing power server is less than the second computing power call threshold, the computing power of the computing power server is surplus, and the data analysis terminal reads and processes the time information of the computing power average distribution information of the computing power server to determine the computing power surplus time interval.

[0034] Preferably, the step of performing analysis and processing on the computing power overload time interval based on the data analysis terminal to determine the task reallocation information specifically includes the following steps:

[0035] Based on the data analysis terminal, a difference calculation is performed on the computing power average distribution information of the computing power overload time interval and the first computing power call threshold to determine the overload computing power information of the computing power server;

[0036] The data analysis terminal performs task retrieval processing on the database system according to the computing power overload time interval to obtain the tasks in the computing power overload time interval;

[0037] Based on the data analysis terminal, perform data analysis and processing on the tasks in the computing power overload time interval to determine the computing power information required for the tasks;

[0038] Based on the data analysis terminal, match the computing power information required for the tasks with the overload computing power information of the computing power server to determine the tasks to be redeployed.

[0039] Preferably, the matching process of the computing power information required for the tasks and the overload computing power information of the computing power server based on the data analysis terminal to determine the tasks to be redeployed specifically includes the following steps:

[0040] The data analysis terminal screens the computing power information required for the tasks with the overload computing power information of the computing power server as the feature;

[0041] If the overload computing power information of the computing power server is less than or equal to the computing power information required for the tasks, the data analysis terminal records the tasks that can be redeployed, and the data analysis terminal eliminates the tasks corresponding to the overload computing power information of the computing power server that is greater than the computing power information required for the tasks;

[0042] Based on the data analysis terminal, perform a difference calculation on the average computing power distribution information in the computing power overload time interval and the computing power information required for the tasks that can be redeployed to obtain the remaining computing power information in the computing power overload time interval;

[0043] Based on the data analysis terminal, judge and process the remaining computing power information in the computing power overload time interval and the second computing power call threshold to determine the tasks to be redeployed.

[0044] Preferably, the judgment process of the remaining computing power information in the computing power overload time interval and the second computing power call threshold based on the data analysis terminal to determine the tasks to be redeployed specifically includes the following steps:

[0045] Based on the data analysis terminal, judge and process the remaining computing power information in the computing power overload time interval and the second computing power call threshold;

[0046] If the remaining computing power information in the computing power overload time interval is greater than or equal to the second computing power call threshold, the tasks that can be redeployed are the tasks to be redeployed;

[0047] If the remaining computing power information in the computing power overload time interval is less than the second computing power call threshold, there is an excess of computing power in the computing power overload time interval, and the data analysis terminal re-selects the tasks that can be redeployed for analysis with the second computing power call threshold to determine the tasks to be redeployed.

[0048] Preferably, the data analysis terminal analyzes and processes the computing power surplus time interval according to the tasks to be redeployed to determine the computing power management plan of the computing power server, which specifically includes the following steps:

[0049] Based on the data analysis terminal, calculate the difference between the average computing power allocation information in the computing power surplus time interval and the first computing power call threshold to determine the adjustable computing power information;

[0050] Based on the data analysis terminal, judge and process the adjustable computing power information and the required computing power information for the reallocation task;

[0051] If the adjustable computing power information is greater than or equal to the required computing power information for the reallocation task, the data analysis terminal allocates the reallocation task to the computing power surplus time interval;

[0052] If the adjustable computing power information is less than the required computing power information for the reallocation task, the data analysis terminal reselects the computing power surplus time interval and the reallocation task for analysis to determine the computing power surplus time interval to which the reallocation task can be allocated.

[0053] Furthermore, a computing power management system for a computing power server based on data analysis is proposed, which is used to implement a computing power management method for a computing power server based on data analysis as described above, including:

[0054] A data analysis terminal, which is used to classify, calculate, analyze, and reallocate the historical operation data of the computing power server, and is used to control data transmission and information interaction between each module;

[0055] A database system, which is used to store the historical operation data of the computing power server and the R & D documents of the computing power server;

[0056] A data classification module, which classifies the historical operation data of the computing power server according to classification features to obtain the first historical operation data and the second historical operation data of the computing power server

[0057] A data calculation module, which is used to calculate and process the computing power allocation information of several groups of computing power servers to determine the average computing power allocation information of the computing power server;

[0058] A threshold determination module, which is used to analyze and process the R & D documents of the computing power server to determine the computing power call threshold;

[0059] A data analysis module, which comprehensively analyzes according to the average computing power allocation information and the computing power call threshold of the computing power server to determine the computing power overload time interval and the computing power surplus time interval;

[0060] A comparison and judgment module, which is used to compare and judge the average computing power distribution information in the computing power overload time interval, the average computing power distribution information in the computing power surplus time interval, and the computing power call threshold, so as to determine the computing power management scheme of the computing power server.

[0061] Compared with the prior art, the present invention provides a computing power management method and system for a computing power server based on data analysis, and has the following beneficial effects:

[0062] First, the present invention analyzes the historical operation data of the computing power server to determine the computing power overload time interval and the computing power surplus time interval of the computing power server. Then, it analyzes the computing power required for the tasks executed in the computing power overload time interval, and transfers some of its tasks to the computing power surplus time interval for execution, avoiding the overload of the computing power server, prolonging the service life of the computing power server, and at the same time, realizing the balanced use of the computing power server. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic flowchart of steps S100 - S500 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0064] Figure 2 It is a schematic flowchart of steps S201 - S204 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0065] Figure 3 It is a schematic flowchart of steps S2041 - S2043 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0066] Figure 4 It is a schematic flowchart of steps S301 - S304 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0067] Figure 5 It is a schematic flowchart of steps S3041 - S3044 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0068] Figure 6 It is a schematic flowchart of steps S401 - S404 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0069] Figure 7 It is a schematic flowchart of steps S4041 - S4044 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0070] Figure 8Schematic diagram of the process of steps S40441 - S40443 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0071] Figure 9 Schematic diagram of the process of steps S501 - S504 in a computing power management method for a computing power server based on data analysis proposed by the present invention;

[0072] Figure 10 Block diagram of the structure of a computing power management system for a computing power server based on data analysis proposed by the present invention. Detailed implementation manners

[0073] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations.

[0074] Refer to Figure 1 As shown, a computing power management method for a computing power server based on data analysis includes:

[0075] S100. Based on a data analysis terminal, extract data from the database system to obtain the historical operation data of the computing power server;

[0076] S200. Based on the data analysis terminal, analyze and process the historical operation data of the computing power server to obtain the computing power average distribution information of the computing power server;

[0077] S300. Based on the data analysis terminal, analyze and process the computing power average distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval;

[0078] S400. Based on the data analysis terminal, analyze and process the computing power overload time interval to determine the task re - allocation;

[0079] S500. The data analysis terminal analyzes and processes the computing power surplus time interval according to the task re - allocation to determine the computing power management scheme of the computing power server;

[0080] Those skilled in the art can understand that when the computing power server executes multiple tasks in a certain time period, it may cause the computing power of the computing power server to be overloaded. When the computing power server is over - used, it may shorten the service life of the computing power server. In order to avoid the situation of shortening the service life of the computing power server, some tasks in the computing power overload time interval are allocated to the computing power surplus time interval for execution, realizing the balanced management of the computing power server. At the same time, the service life of the computing power server is also extended.

[0081] Refer to Figure 2As shown, based on the data analysis terminal, analyzing and processing the historical operation data of the computing power server to obtain the computing power average distribution information of the computing power server specifically includes the following steps:

[0082] S201. The data analysis terminal classifies the historical operation data of the computing power server by date to obtain the first historical operation data of the computing power server;

[0083] S202. The data analysis terminal performs secondary classification processing on the first historical operation data of the computing power server by hour to obtain the second historical operation data of the computing power server;

[0084] S203. Based on the data analysis terminal, analyzing and processing the second historical operation data of the computing power server to obtain several groups of computing power distribution information of the computing power server;

[0085] S204. Based on the data analysis terminal, analyzing and processing several groups of computing power distribution information of the computing power server to obtain the computing power average distribution information of the computing power server.

[0086] Refer to Figure 3 As shown, based on the data analysis terminal, analyzing and processing several groups of computing power distribution information of the computing power server to obtain the computing power average distribution information of the computing power server specifically includes the following steps:

[0087] S2041. The data analysis terminal classifies the computing power analysis information of several groups of computing power servers by the same time to determine the computing power distribution information of the computing power server at the same time;

[0088] S2042. Based on the data analysis terminal, performing a summation calculation on the computing power distribution information of the computing power server at the same time to determine the total computing power usage data of the computing power server at the same time;

[0089] S2043. Based on the data analysis terminal, performing calculation processing on the total computing power usage data of the computing power server at the same time to obtain the computing power average distribution information of the computing power server;

[0090] Among them, the specific calculation formula for obtaining the computing power average distribution information of the computing power server is:

[0091]

[0092] In the formula, C1 is the computing power average distribution information of the computing power server; C i is the computing power usage data of the computing power server at the same time; n is the specific quantity of the computing power usage data of the computing power server at the same time;

[0093] In this embodiment, the computing power server may execute the same tasks every day, but some tasks may be executed within the same time period, resulting in different computing power usage of the computing power server in each time period. Therefore, the historical operation data of the computing power server is classified according to time characteristics, and then the computing power in each time period is summed and averaged to determine the average distribution information of the computing power of the computing power server in each time period. Finally, the average distribution information of the computing power of the computing power server in each time period is judged to determine the computing power overload time interval and the computing power surplus time interval.

[0094] Referring to Figure 4 As shown, based on the data analysis terminal, analyzing and processing the average distribution information of the computing power of the computing power server to determine the computing power overload time interval and the computing power surplus time interval specifically includes the following steps:

[0095] S301. Based on the data analysis terminal, call the parameters of the computing power server to determine the model of the computing power server;

[0096] S302. The data analysis terminal retrieves information from the database system according to the model of the computing power server to obtain the R & D documents of the computing power server;

[0097] S303. Based on the data analysis terminal, perform data analysis and processing on the R & D documents of the computing power server to determine the computing power call threshold, where the computing power call threshold includes a first computing power call threshold and a second computing power call threshold;

[0098] S304. Based on the data analysis terminal, perform a comparison and judgment process on the computing power call threshold and the average distribution information of the computing power of the computing power server to determine the computing power overload time interval and the computing power surplus time interval.

[0099] Referring to Figure 5 As shown, based on the data analysis terminal, performing a comparison and judgment process on the computing power call threshold and the average distribution information of the computing power of the computing power server to determine the computing power overload time interval and the computing power surplus time interval specifically includes the following steps:

[0100] S3041. Based on the data analysis terminal, perform a judgment process on the computing power call threshold and the average distribution information of the computing power of the computing power server;

[0101] S3042. If the average distribution information of the computing power of the computing power server is greater than or equal to the first computing power call threshold, the computing power of the computing power server is called too much, and the data analysis terminal reads and processes the time information of the average distribution information of the computing power of the computing power server to determine the computing power overload time interval;

[0102] S3043. If the average computing power distribution information of the computing power server is less than the first threshold of computing power invocation and greater than or equal to the second threshold of computing power invocation, the computing power invocation of the computing power server is normal;

[0103] S3044. If the average computing power distribution information of the computing power server is less than the second threshold of computing power invocation, the computing power of the computing power server is excessive. The data analysis terminal reads and processes the time information of the average computing power distribution information of the computing power server to determine the excessive computing power time interval;

[0104] In this embodiment, in order to achieve the balanced use of the computing power server, some tasks within a certain time period are transferred to other time periods for execution, that is, the tasks within the computing power overload time interval are allocated to the excessive computing power time interval for execution. The above method can not only achieve the balanced use of the computing power server, but also avoid the situation of computing power overload of the computing power server, and at the same time can extend the service life of the computing power server.

[0105] Refer to Figure 6 As shown, based on the data analysis terminal, the analysis and processing of the computing power overload time interval to determine the task reallocation information specifically includes the following steps:

[0106] S401. Based on the data analysis terminal, calculate the difference between the average computing power distribution information of the computing power overload time interval and the first threshold of computing power invocation to determine the overload computing power information of the computing power server;

[0107] S402. The data analysis terminal retrieves tasks from the database system according to the computing power overload time interval to obtain the tasks in the computing power overload time interval;

[0108] S403. Based on the data analysis terminal, perform data analysis processing on the tasks in the computing power overload time interval to determine the computing power information required by the tasks;

[0109] S404. Based on the data analysis terminal, perform matching processing on the computing power information required by the tasks and the overload computing power information of the computing power server to determine the reallocated tasks.

[0110] Refer to Figure 7 As shown, based on the data analysis terminal, the matching processing of the computing power information required by the tasks and the overload computing power information of the computing power server to determine the reallocated tasks specifically includes the following steps:

[0111] S4041. The data analysis terminal screens the computing power information required by the tasks with the overload computing power information of the computing power server as the feature;

[0112] S4042. If the overload computing power information of the computing power server is less than or equal to the computing power information required by the task, the data analysis terminal records the task that can be allocated, and the data analysis terminal eliminates the task corresponding to the overload computing power information of the computing power server that is greater than the computing power information required by the task;

[0113] S4043. Based on the data analysis terminal, perform a subtraction calculation on the average computing power distribution information in the computing power overload time interval and the computing power information required by the task that can be allocated to obtain the remaining computing power information in the computing power overload time interval;

[0114] S4044. Based on the data analysis terminal, perform a judgment process on the remaining computing power information in the computing power overload time interval and the second computing power call threshold to determine the task to be reallocated;

[0115] In this embodiment, in order to avoid the overload of the computing power server, the computing power of the task to be allocated is calculated, that is, the task allocated to the computing power surplus time interval cannot cause the overload of the computing power server. Therefore, by performing a judgment process on the remaining computing power information in the computing power overload time interval and the second computing power call threshold, the task to be reallocated is determined to achieve the balanced use of the computing power server.

[0116] Refer to Figure 8 As shown, based on the data analysis terminal, performing a judgment process on the remaining computing power information in the computing power overload time interval and the second computing power call threshold to determine the task to be reallocated specifically includes the following steps:

[0117] S40441. Based on the data analysis terminal, perform a judgment process on the remaining computing power information in the computing power overload time interval and the second computing power call threshold;

[0118] S40442. If the remaining computing power information in the computing power overload time interval is greater than or equal to the second computing power call threshold, the task that can be allocated is the task to be reallocated;

[0119] S40443. If the remaining computing power information in the computing power overload time interval is less than the second computing power call threshold, the computing power in the computing power overload time interval is in surplus. The data analysis terminal reselects the task that can be allocated and analyzes it with the second computing power call threshold to determine the task to be reallocated.

[0120] Refer to Figure 9 As shown, the data analysis terminal analyzes and processes the computing power surplus time interval according to the task to be reallocated. The specific steps for determining the computing power management plan of the computing power server include the following:

[0121] S501. Based on the data analysis terminal, perform a subtraction calculation on the average computing power distribution information in the computing power surplus time interval and the first computing power call threshold to determine the allocable computing power information;

[0122] S502. Based on the data analysis terminal, judge and process the available computing power information and the required computing power information for the reallocation task.

[0123] S503. If the available computing power information is greater than or equal to the required computing power information for the reallocation task, the data analysis terminal allocates the reallocation task to the time interval with excess computing power.

[0124] S504. If the available computing power information is less than the required computing power information for the reallocation task, the data analysis terminal reselects the time interval with excess computing power and analyzes it with the reallocation task to determine the time interval with excess computing power to which the reallocation task can be allocated.

[0125] In this embodiment, when the task to be reallocated needs to be executed within the time interval with excess computing power, it may cause the time interval with excess computing power to become a time interval with overloaded computing power, and if the computing power server is overloaded, it will lead to a reduction in the service life of the computing power server. Therefore, by comparing and judging the available computing power information in the time interval with excess computing power and the required computing power information for the reallocation task, it is ensured that the time interval with excess computing power will not become a time interval with overloaded computing power, realizing the balanced use of the computing power server.

[0126] Refer to Figure 10 As shown in the figure, a computing power management system for a computing power server based on data analysis is used to implement a computing power management method for a computing power server based on data analysis as described above, including:

[0127] A data analysis terminal, which is used to classify, calculate, analyze, and reallocate the historical operation data of the computing power server, and is used to control data transmission and information interaction between each module.

[0128] A database system, which is used to store the historical operation data of the computing power server and the R & D documents of the computing power server.

[0129] A data classification module, which classifies the historical operation data of the computing power server according to classification features to obtain the first historical operation data and the second historical operation data of the computing power server.

[0130] A data calculation module, which is used to calculate and process the computing power allocation information of several groups of computing power servers to determine the average computing power allocation information of the computing power server.

[0131] A threshold determination module, which is used to analyze and process the R & D documents of the computing power server to determine the computing power call threshold.

[0132] A data analysis module, which comprehensively analyzes according to the average computing power distribution information and the computing power call threshold of the computing power server to determine the computing power overload time interval and the computing power surplus time interval;

[0133] A comparison and judgment module, which is used to compare and judge the average computing power distribution information in the computing power overload time interval, the average computing power distribution information in the computing power surplus time interval and the computing power call threshold to determine the computing power management scheme of the computing power server.

[0134] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A computing power management method for a computing power server based on data analysis, characterized in that, Including: Based on the data analysis terminal, extract data from the database system to obtain the historical operation data of the computing power server; Based on the data analysis terminal, analyze and process the historical operation data of the computing power server to obtain the average computing power distribution information of the computing power server; Based on the data analysis terminal, analyze and process the average computing power distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval; Based on the data analysis terminal, analyze and process the computing power overload time interval to determine the task of reallocation; The data analysis terminal analyzes and processes the computing power surplus time interval according to the reallocation task to determine the computing power management plan of the computing power server.

2. The computing power management method of a computing power server based on data analysis according to claim 1, characterized in that The step of, based on the data analysis terminal, analyzing and processing the historical operation data of the computing power server to obtain the average computing power distribution information of the computing power server specifically includes the following steps: The data analysis terminal classifies the historical operation data of the computing power server by date to obtain the first historical operation data of the computing power server; The data analysis terminal performs secondary classification processing on the first historical operation data of the computing power server by hour to obtain the second historical operation data of the computing power server; Based on the data analysis terminal, analyze and process the second historical operation data of the computing power server to obtain several groups of computing power distribution information of the computing power server; Based on the data analysis terminal, analyze and process several groups of computing power distribution information of the computing power server to obtain the average computing power distribution information of the computing power server.

3. The computing power management method of a computing power server based on data analysis according to claim 2, characterized in that, The step of, based on the data analysis terminal, analyzing and processing several groups of computing power distribution information of the computing power server to obtain the average computing power distribution information of the computing power server specifically includes the following steps: The data analysis terminal classifies the computing power analysis information of several groups of computing power servers by the same time to determine the computing power distribution information of the computing power servers at the same time; Based on the data analysis terminal, perform a summation calculation on the computing power distribution information of the computing power servers at the same time to determine the total computing power usage data of the computing power servers at the same time; Based on the data analysis terminal, perform calculation processing on the total computing power usage data of the computing power servers at the same time to obtain the average computing power distribution information of the computing power server; Among them, the specific calculation formula for obtaining the average computing power distribution information of the computing power server is: In the formula, C1 is the average allocation information of the computing power of the computing power server; C i is the computing power usage data of the computing power server at the same time; n is the specific quantity of the computing power usage data of the computing power server at the same time.

4. A computing power management method for a computing power server based on data analysis according to claim 1, characterized in that, The step of, based on the data analysis terminal, analyzing and processing the average computing power distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval specifically includes the following steps: Based on the data analysis terminal, call parameters of the computing power server to determine the model of the computing power server; The data analysis terminal retrieves information from the database system according to the model of the computing power server to obtain the R & D documents of the computing power server; Based on the data analysis terminal, perform data analysis processing on the R & D documents of the computing power server to determine the computing power call threshold, where the computing power call threshold includes a first computing power call threshold and a second computing power call threshold; Based on the data analysis terminal, perform a comparison and judgment process on the computing power call threshold and the average computing power distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval.

5. The computing power management method of a computing power server based on data analysis according to claim 4, characterized in that, The data analysis terminal compares and judges the computing power call threshold and the average computing power distribution information of the computing power server to determine the computing power overload time interval and the computing power surplus time interval, which specifically includes the following steps: Based on the data analysis terminal, judge and process the computing power call threshold and the average computing power distribution information of the computing power server; If the average computing power distribution information of the computing power server is greater than or equal to the first computing power call threshold, the computing power of the computing power server is called too much. The data analysis terminal reads and processes the time information of the average computing power distribution information of the computing power server to determine the computing power overload time interval; If the average computing power distribution information of the computing power server is less than the first computing power call threshold and the average computing power distribution information of the computing power server is greater than or equal to the second computing power call threshold, the computing power of the computing power server is called normally; If the average computing power distribution information of the computing power server is less than the second computing power call threshold, the computing power of the computing power server is surplus. The data analysis terminal reads and processes the time information of the average computing power distribution information of the computing power server to determine the computing power surplus time interval.

6. The computing power management method of a computing power server based on data analysis according to claim 1, characterized in that, The data analysis terminal analyzes and processes the computing power overload time interval to determine the task redeployment information, which specifically includes the following steps: Based on the data analysis terminal, calculate the difference between the average computing power distribution information of the computing power overload time interval and the first computing power call threshold to determine the overload computing power information of the computing power server; The data analysis terminal retrieves tasks from the database system according to the computing power overload time interval to obtain the tasks in the computing power overload time interval; Based on the data analysis terminal, perform data analysis processing on the tasks in the computing power overload time interval to determine the computing power information required for the tasks; Based on the data analysis terminal, match the computing power information required for the tasks and the overload computing power information of the computing power server to determine the redeployed tasks.

7. A computing power management method for a computing power server based on data analysis according to claim 6, characterized in that The data analysis terminal matches the computing power information required for the tasks and the overload computing power information of the computing power server to determine the redeployed tasks, which specifically includes the following steps: The data analysis terminal screens the computing power information required for the tasks with the overload computing power information of the computing power server as the feature; If the overload computing power information of the computing power server is less than or equal to the computing power information required for the tasks, the data analysis terminal records the deployable tasks, and the data analysis terminal eliminates the tasks corresponding to the overload computing power information of the computing power server being greater than the computing power information required for the tasks; Based on the data analysis terminal, calculate the difference between the average computing power distribution information of the computing power overload time interval and the computing power information required for the deployable tasks to obtain the remaining computing power information of the computing power overload time interval; Based on the data analysis terminal, judge and process the remaining computing power information of the computing power overload time interval and the second computing power call threshold to determine the redeployed tasks.

8. A computing power management method for a computing power server based on data analysis according to claim 7, characterized in that, The data analysis terminal judges and processes the remaining computing power information of the computing power overload time interval and the second computing power call threshold to determine the redeployed tasks, which specifically includes the following steps: Based on the data analysis terminal, judge and process the remaining computing power information of the computing power overload time interval and the second computing power call threshold; If the remaining computing power information in the computing power overload time interval is greater than or equal to the second computing power call threshold, the task to be allocated is a reallocation task; If the remaining computing power information in the computing power overload time interval is less than the second computing power call threshold, there is an excess of computing power in the computing power overload time interval. The data analysis terminal reselects the task to be allocated and the second computing power call threshold for analysis to determine the reallocation task.

9. The computing power management method of a computing power server based on data analysis according to claim 1, characterized in that, The data analysis terminal analyzes and processes the computing power surplus time interval according to the reallocation task to determine the computing power management plan of the computing power server, which specifically includes the following steps: Based on the data analysis terminal, calculate the difference between the average computing power distribution information in the computing power surplus time interval and the first computing power call threshold to determine the available computing power information; Based on the data analysis terminal, judge and process the available computing power information and the required computing power information of the reallocation task; If the available computing power information is greater than or equal to the required computing power information of the reallocation task, the data analysis terminal allocates the reallocation task to the computing power surplus time interval; If the available computing power information is less than the required computing power information of the reallocation task, the data analysis terminal reselects the computing power surplus time interval and the reallocation task for analysis to determine the computing power surplus time interval to which the reallocation task can be allocated.

10. A computing power management system for a computing power server based on data analysis, which is used to implement a computing power management method for a computing power server based on data analysis as described in any one of claims 1-9, characterized in that, Including: A data analysis terminal, which is used to classify, calculate, analyze, and reallocate the historical operation data of the computing power server. The data analysis terminal is used to control data transmission and information interaction between each module; A database system, which is used to store the historical operation data of the computing power server and the R & D documents of the computing power server; A data classification module, which classifies the historical operation data of the computing power server according to classification features to obtain the first historical operation data of the computing power server and the second historical operation data of the computing power server; A data calculation module, which is used to calculate and process the computing power distribution information of several groups of computing power servers to determine the average computing power distribution information of the computing power server; A threshold determination module, which is used to analyze and process the R & D documents of the computing power server to determine the computing power call threshold; A data analysis module, which comprehensively analyzes according to the average computing power distribution information and the computing power call threshold of the computing power server to determine the computing power overload time interval and the computing power surplus time interval; A comparison and judgment module, which is used to compare and judge the average computing power distribution information in the computing power overload time interval, the average computing power distribution information in the computing power surplus time interval, and the computing power call threshold to determine the computing power management plan of the computing power server.

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