Capacity Evaluation Parameter Control Method and System

Abstract

The present application provides a method and system for controlling capacity evaluation parameters. The method includes: the capacity evaluation parameter control device can interact with the device under test to obtain at least one system parameter of each device under test and the parameter value of each system parameter. The capacity evaluation parameter control device can input the parameter values of at least one system parameter of a device under test into a preset tuning algorithm. The capacity evaluation parameter control device can obtain the parameter values of at least one evaluation parameter of the device under test through the preset tuning algorithm. The capacity evaluation parameter control device can generate a capacity evaluation use case for the device under test according to the combination of parameter values predicted by the preset tuning algorithm. The method of the present application improves the generation efficiency of the evaluation parameters and improves the evaluation accuracy and evaluation efficiency of the device under test.

Description

Technical Field

[0001] This application relates to the field of computers, and in particular, to a method and system for controlling capacity evaluation parameters. Background Art

[0002] Capacity evaluation is a branch direction of performance testing. Capacity evaluation usually evaluates the maximum load capacity of the software and hardware systems under test through Benchmark. The parameter combination of Benchmark will determine the evaluation effect of this capacity evaluation. An inappropriate parameter combination may cause Benchmark to be unable to generate sufficient pressure data to evaluate the true capacity of the software and hardware systems.

[0003] In order to improve the efficiency of capacity evaluation, in the prior art, technicians usually need to determine the parameter combination of Benchmark according to manual experience to achieve the capacity evaluation of the software and hardware systems under test. Moreover, for the software and hardware systems under test of different models, the parameters of CPU, memory, IO, network, etc. are usually different. Technicians need to determine different parameter combinations according to the software and hardware systems under test of different models to achieve the optimal capacity evaluation effect.

[0004] However, there is a problem of low parameter formulation efficiency in the parameter combination of capacity evaluation formulated by manual experience. Summary of the Invention

[0005] This application provides a method and system for controlling capacity evaluation parameters to solve the problem of low parameter formulation efficiency existing in the prior art.

[0006] In a first aspect, this application provides a method for controlling capacity evaluation parameters, including:

[0007] Obtain the parameter values of at least one system parameter of the device under test;

[0008] Determine the parameter values of at least one evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and a preset tuning algorithm;

[0009] Generate a capacity evaluation case for the device under test according to the parameter values of at least one evaluation parameter, and the capacity evaluation case is used to evaluate the capacity of the device under test.

[0010] Optionally, determining the parameter values of at least one evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and a preset tuning algorithm specifically includes:

[0011] Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test;

[0012] Determine the parameter values of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and the preset tuning algorithm.

[0013] Optionally, determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test, specifically including:

[0014] For each evaluation parameter, obtain the calculation model corresponding to the evaluation parameter, and input the parameter values of the system parameter into the calculation model corresponding to the evaluation parameter to calculate and obtain the parameter adjustment range of the evaluation parameter.

[0015] Optionally, determine the parameter values of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and the preset tuning algorithm, specifically including:

[0016] Generate a parameter matrix according to the parameter adjustment ranges of the respective evaluation parameters;

[0017] Input the parameter matrix into the preset tuning algorithm to obtain the parameter values of each of the evaluation parameters among the evaluation parameters.

[0018] Optionally, the method further includes:

[0019] Evaluate the device under test using the capacity evaluation use case corresponding to the device under test to obtain an evaluation result;

[0020] Determine the evaluation index of the device under test according to the evaluation result, where the evaluation index is used to indicate the true capacity of the device under test.

[0021] Optionally, the at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

[0022] In a second aspect, the present application provides a capacity evaluation parameter control system, including:

[0023] An acquisition module, configured to acquire the parameter values of at least one system parameter of the device under test;

[0024] A control module, configured to determine the parameter values of at least one evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and a preset tuning algorithm; generate a capacity evaluation use case for the device under test according to the parameter values of the at least one evaluation parameter, where the capacity evaluation use case is used to evaluate the capacity of the device under test.

[0025] Optionally, the control module is specifically configured to:

[0026] Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test;

[0027] Determine the parameter values of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and the preset optimization algorithm.

[0028] Optionally, the control module is specifically configured to:

[0029] For each evaluation parameter, obtain the calculation model corresponding to the evaluation parameter, and input the parameter value of the system parameter into the calculation model corresponding to the evaluation parameter to calculate and obtain the parameter adjustment range of the evaluation parameter.

[0030] Optionally, the control module is specifically configured to:

[0031] Generate a parameter matrix according to the parameter adjustment ranges of the respective evaluation parameters;

[0032] Input the parameter matrix into the preset optimization algorithm to obtain the parameter values of each of the evaluation parameters among the evaluation parameters.

[0033] Optionally, the system further includes:

[0034] An evaluation module, configured to evaluate the device under test using the capacity evaluation use case corresponding to the device under test to obtain an evaluation result; and determine an evaluation index of the device under test according to the evaluation result, where the evaluation index is used to indicate the true capacity of the device under test.

[0035] Optionally, the at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

[0036] In a third aspect, the present application provides a capacity evaluation parameter control device, including: a memory, a processor, etc.;

[0037] The memory is used to store a computer program; the processor is configured to execute the capacity evaluation parameter control method in the first aspect and any possible design of the first aspect according to the computer program stored in the memory.

[0038] In a fourth aspect, the present application provides a readable storage medium, in which a computer program is stored. When at least one processor of the capacity evaluation parameter control device executes the computer program, the capacity evaluation parameter control device executes the capacity evaluation parameter control method in the first aspect and any possible design of the first aspect.

[0039] Fifth aspect, the present application provides a computer program product, which includes a computer program. When at least one processor of the capacity evaluation parameter control device executes this computer program, the capacity evaluation parameter control device executes the capacity evaluation parameter control method in the first aspect and any possible design of the first aspect.

[0040] The capacity evaluation parameter control method provided by the present application obtains at least one system parameter of each device under test and the parameter value of each system parameter by interacting with the device under test; inputs the parameter values of at least one system parameter of a device under test into a preset tuning algorithm; through this preset tuning algorithm, obtains the parameter values of at least one evaluation parameter of this device under test; and generates a capacity evaluation use case for the device under test according to the parameter value combination predicted by the preset tuning algorithm, thereby realizing the generation of personalized evaluation parameters for the device under test, improving the generation efficiency of the evaluation parameters, avoiding the redundancy of capacity evaluation use cases caused by multiple groups of evaluation parameters, and improving the evaluation accuracy and evaluation efficiency of this device under test. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 It is a schematic diagram of a scenario for manually formulating a capacity evaluation use case provided by the prior art;

[0043] Figure 2 It is a schematic diagram of a scenario for capacity evaluation parameter control provided by an embodiment of the present application;

[0044] Figure 3 It is a flowchart of a capacity evaluation parameter control method provided by an embodiment of the present application;

[0045] Figure 4 It is a flowchart of a capacity evaluation parameter control method provided by an embodiment of the present application;

[0046] Figure 5 It is a schematic diagram of the structure of a capacity evaluation parameter control system provided by an embodiment of the present application;

[0047] Figure 6 It is a schematic diagram of the hardware structure of a capacity evaluation parameter control device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] To make the objectives, technical solutions and advantages of this application clearer, the following will, with reference to the accompanying drawings in this application, clearly and completely describe the technical solutions in this application. Apparently, the described embodiments are some but not all of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0049] The terms "first", "second", "third", "fourth", etc. in the description and claims of this application and the above accompanying drawings are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances. For example, without departing from the scope of this article, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information.

[0050] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining".

[0051] Furthermore, as used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms unless the context indicates otherwise.

[0052] It should be further understood that the terms "comprising", "including" indicate the presence of features, steps, operations, elements, components, items, types, and / or groups, but do not exclude the presence, occurrence or addition of one or more other features, steps, operations, elements, components, items, types, and / or groups.

[0053] The term "or" and "and / or" as used herein are interpreted inclusively and mean any one or any combination. Thus, "A, B or C" or "A, B and / or C" means "any one of the following: A; B; C; A and B; A and C; B and C; A, B and C". An exception to this definition only occurs when the combination of elements, functions, steps or operations is inherently mutually exclusive in some way.

[0054] Capacity assessment is a branch direction of performance testing. Capacity assessment usually evaluates the maximum load capacity of the software and hardware systems under test through Benchmark. Specifically, capacity assessment is a method of testing and evaluating the maximum processing capacity of requests when the system is in the maximum load state or a certain indicator reaches the maximum acceptable threshold through Benchmark. Among them, Benchmark is the benchmark program. This benchmark program is an evaluation program used to estimate the performance of the tuned application and give a performance score. After the evaluation is completed, users can use the evaluation results obtained to assist in completing tasks such as new model verification comparison, machine procurement, and solution. For example, the evaluation results can be used to determine whether the business carrying capacity of the current cluster / data center meets the requirements. Another example is that the machine type, quantity and other information to be purchased can be determined according to the evaluation results.

[0055] In the prior art, different devices under test usually have different system parameters. The system parameters can be configuration items that can be dynamically set in the operating system and affect the application performance, such as kernel configuration parameters and application configuration parameters. When the user sets different system parameters in the device under test, the score of the device under test on a certain benchmark program will change. For example, the system parameters can include CPU, memory, IO, network, etc. Technicians can specify several parameter combinations of Benchmark according to the system parameters of the device under test and manual experience. The capacity assessment parameter control device can implement the capacity assessment of the software and hardware systems under test according to these parameter combinations of Benchmark. During the capacity assessment process, the parameter combination of Benchmark will determine the evaluation effect of this capacity assessment. An inappropriate parameter combination may cause Benchmark to fail to generate sufficient pressure data to evaluate the true capacity of the software and hardware systems. For example, on different models, a fixed parameter combination may not necessarily enable Benchmark to generate sufficient pressure data, which will lead to the inability to evaluate the true capacity of the software and hardware. Therefore, technicians need to determine different parameter combinations according to the software and hardware systems under test of different models to achieve the optimal capacity assessment effect.

[0056] However, when technicians formulate the parameter combination of capacity assessment based on experience, such as Figure 1As shown in the figure, in order to evaluate the capacity of different environments as accurately as possible, multiple sets of parameter combinations are often set. However, the setting of these multiple sets of parameter combinations can easily lead to redundancy of test cases and an increase in test time consumption, resulting in low evaluation efficiency. In addition, these multiple sets of parameter combinations still cannot adapt to all devices. For example, when used on small-sized devices under test, these multiple sets of parameter combinations are prone to excessive pressure, causing the machine to hang. Also, when used on large-sized devices under test, these multiple sets of parameter combinations are likely to result in insufficient pressure, making it impossible to effectively evaluate the true capacity of the device under test. Moreover, once a new model or new software becomes the device under test, technicians often need to manually adapt the test cases or write new test cases, resulting in high maintenance costs.

[0057] To address the above problems, the present application proposes a method for controlling capacity evaluation parameters. The present application proposes a Benchmark evaluation parameter control method based on a hyperparameter tuning algorithm. This hyperparameter-based parameter tuning algorithm can continuously provide better combinations of evaluation parameters through a certain algorithm strategy, thereby finding a better parameter configuration for evaluation. In addition, the present application also realizes an intelligent control method for evaluation parameters for different devices under test by detecting the system parameters of the device under test. By detecting the device under test, the present application can obtain system parameters of hardware resources such as CPU parameters, memory parameters, IO parameters, and network parameters. These system parameters can provide a parameter adjustment range for the evaluation parameters of Benchmark. The present application can select appropriate parameter values from the parameter adjustment range of the evaluation parameters of Benchmark through the hyperparameter tuning algorithm to form different combinations of evaluation parameters. The present application can generate capacity evaluation test cases for the device under test according to this combination of evaluation parameters. These capacity evaluation test cases are test cases customized by the capacity evaluation parameter control device for different software and hardware environments, and can effectively detect the true capacity of different devices under test.

[0058] The present application realizes the generation of customized parameter combinations and customized capacity evaluation test cases in different software and hardware environments through the above solutions. These capacity evaluation test cases can generate sufficient pressure to evaluate the true capacity of the environment, greatly improving the parameter setting efficiency. In addition, by customizing the generation of capacity evaluation test cases, the present application reduces the redundancy problem caused by using the same set of evaluation test cases in different environments, effectively reducing the manual maintenance cost and greatly improving the evaluation efficiency.

[0059] The technical solution of the present application will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0060] Figure 2The figure shows a schematic diagram of a scenario for controlling capacity evaluation parameters provided by an embodiment of the present application. As Figure 2 shown, a capacity evaluation parameter control device can correspond to multiple devices under test. The capacity evaluation parameter control device can obtain the software and hardware system parameters of each device under test from each device under test. Multiple calculation models of evaluation parameters can be preset in the capacity evaluation parameter control device. The capacity evaluation parameter control device can determine the parameter adjustment range of the evaluation parameters of each device under test according to the system parameters of each device under test. The capacity evaluation parameter control device can also input the system parameters of each device under test and the multiple evaluation parameters preset in the capacity evaluation parameter control device into a preset tuning algorithm. The capacity evaluation parameter control device can determine the parameter values of at least one evaluation parameter of each device under test through the preset tuning algorithm. The capacity evaluation parameter control device can generate a capacity evaluation use case for each device under test according to the parameter values of at least one evaluation parameter of each device under test. The capacity evaluation parameter control device can use the capacity evaluation use case to evaluate the capacity of the device under test. For example, as Figure 2 shown, after the capacity evaluation parameter control device obtains the system parameters of Device Under Test 1, the corresponding generated capacity evaluation use case can be used to evaluate the capacity of Device Under Test 1.

[0061] In the present application, with the capacity evaluation parameter control device as the execution subject, the capacity evaluation parameter control method of the following embodiments is executed. Specifically, the execution subject can be the hardware device of the capacity evaluation parameter control device, or the software application in the capacity evaluation parameter control device that implements the following embodiments, or the computer-readable storage medium installed with the software application that implements the following embodiments, or the code of the software application that implements the following embodiments.

[0062] Figure 3 The figure shows a flowchart of a capacity evaluation parameter control method provided by an embodiment of the present application. On the basis of the embodiment shown in Figure 2 as Figure 3 shown, with the capacity evaluation parameter control device as the execution subject, the method of this embodiment can include the following steps:

[0063] S101. Obtain the parameter values of at least one system parameter of the device under test.

[0064] In this embodiment, a capacity evaluation parameter control device can communicate with multiple devices under test. The capacity evaluation parameter control device can obtain at least one system parameter and the parameter value of each system parameter of each device under test by interacting with the device under test. Among them, these system parameters can be CPU parameters, memory parameters, IO parameters, network parameters, etc.

[0065] S102. Determine the parameter values of at least one evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and a preset tuning algorithm.

[0066] In this embodiment, the capacity evaluation parameter control device may input the parameter values of at least one system parameter of a device under test into a preset tuning algorithm. The capacity evaluation parameter control device may obtain the parameter values of at least one evaluation parameter of the device under test through the preset tuning algorithm. When the capacity evaluation parameter control device corresponds to multiple devices under test, the capacity evaluation parameter control device may input the parameter values of at least one system parameter of each device under test into the preset tuning algorithm one by one, so as to calculate the parameter values of at least one evaluation parameter of each device under test. The preset tuning algorithm may be a hyperparameter tuning algorithm.

[0067] In one example, the specific process for the capacity evaluation parameter control device to calculate the parameter values of at least one evaluation parameter may include the following steps:

[0068] Step 1. Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test.

[0069] In this step, the capacity evaluation parameter control device may store an evaluation parameter set. The evaluation parameter set may include at least one evaluation parameter and the calculation model of each evaluation. After obtaining the parameter values of at least one system parameter of a device under test, the capacity evaluation parameter control device may calculate the parameter adjustment range of the evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and the preset calculation model of the evaluation parameter. For example, the system parameter is the CPU parameter, and the parameter value of the CPU parameter is used to indicate the number of CPUs / processors in the device under test. The process parameter in the evaluation parameter may be calculated according to the CPU parameter. The capacity evaluation parameter control device may determine that the lower limit of the process parameter is 0.5 * the number of CPUs and the upper limit is 10 * the number of CPUs according to the preset calculation model. For example, when the CPU parameter in the device under test is 4, the lower limit of the process parameter is 2 and the upper limit is 40. That is, the parameter adjustment range of the process parameter of the device under test is [2, 40].

[0070] Step 2. Determine the parameter values of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and the preset tuning algorithm.

[0071] In this step, after determining the parameter adjustment ranges of at least one evaluation parameter, the capacity evaluation parameter control device can input the parameter adjustment ranges of these evaluation parameters into a preset tuning algorithm. The capacity evaluation parameter control device can use this preset tuning algorithm to determine the combination of parameter values of the optimal evaluation parameter among them. When the capacity evaluation parameter control device generates capacity evaluation cases using these combinations of parameter values, the test efficiency will reach the optimal level.

[0072] In one implementation, the capacity evaluation parameter control device can generate a parameter matrix according to the parameter adjustment ranges of these evaluation parameters. Among them, each evaluation parameter can be represented by a row in the parameter matrix. For example, the vector of the row corresponding to the process parameter can be expressed as [2, 40]. The capacity evaluation parameter control device can input this parameter matrix into the preset tuning algorithm to preset the parameter values of each evaluation parameter among the evaluation parameters. The combination of parameter values composed of the parameter values of these evaluation parameters.

[0073] S103. Generate a capacity evaluation case for the device under test according to the parameter values of at least one evaluation parameter. The capacity evaluation case is used to evaluate the capacity of the device under test.

[0074] In this embodiment, the capacity evaluation parameter control device can generate a capacity evaluation case for the device under test according to the combination of parameter values predicted by the preset tuning algorithm. For example, when the parameter value of the process parameter is 10, the number of concurrent processes in the corresponding generated capacity evaluation test case can be 10. The capacity evaluation parameter control device can use this capacity evaluation case to evaluate the capacity of the device under test, so as to determine the true capacity of the device under test.

[0075] For the capacity evaluation parameter control method provided by this application, the capacity evaluation parameter control device can obtain at least one system parameter of each device under test and the parameter value of each system parameter by interacting with the device under test. The capacity evaluation parameter control device can input the parameter values of at least one system parameter of a device under test into the preset tuning algorithm. The capacity evaluation parameter control device can obtain the parameter values of at least one evaluation parameter of the device under test through this preset tuning algorithm. The capacity evaluation parameter control device can generate a capacity evaluation case for the device under test according to the combination of parameter values predicted by the preset tuning algorithm. In this application, by obtaining the system parameters of the device under test, the generation of personalized evaluation parameters for the device under test is realized, the generation efficiency of the evaluation parameters is improved, the redundancy of capacity evaluation cases caused by multiple groups of evaluation parameters is avoided, and the evaluation accuracy and evaluation efficiency of the device under test are improved.

[0076] Figure 4 Shows a flowchart of a capacity evaluation parameter control method provided by an embodiment of this application. In Figure 2 and Figure 3Based on the illustrated embodiments, as Figure 4 shown, with the device for controlling capacity evaluation parameters as the execution entity, the method of this embodiment may include the following steps:

[0077] S201. Obtain the parameter values of at least one system parameter of the device under test.

[0078] S202. Determine the parameter values of at least one evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and a preset tuning algorithm.

[0079] S203. Generate a capacity evaluation use case for the device under test according to the parameter values of at least one evaluation parameter, and the capacity evaluation use case is used to evaluate the capacity of the device under test.

[0080] Among them, steps S201 to S203 are similar to the implementation manners of steps S101 to S103 in the Figure 2 embodiment, and will not be elaborated here in this embodiment.

[0081] S204. Evaluate the device under test using the capacity evaluation use case corresponding to the device under test to obtain an evaluation result.

[0082] In this embodiment, after generating the capacity evaluation use case, the device for controlling capacity evaluation parameters may generate a test request according to the capacity evaluation use case. The device for controlling capacity evaluation parameters may send these test requests to the device under test to implement the processing ability of the device under test for requests when it is in the maximum load state or a certain index reaches the maximum threshold that can be accepted. The device for controlling capacity evaluation parameters may obtain the processing result fed back by the device under test. The device for controlling capacity evaluation parameters may statistically obtain an evaluation result according to the processing result. For example, the evaluation result may include information such as the number of requests completed for processing and the average waiting duration.

[0083] S205. Determine the evaluation index of the device under test according to the evaluation result, and the evaluation index is used to indicate the true capacity of the device under test.

[0084] In this embodiment, the device for controlling capacity evaluation parameters may calculate the true capacity of the device under test according to the statistically obtained evaluation result. The true capacity is the number of requests that the device under test is estimated to be able to process in the maximum load state or when a certain index reaches the maximum threshold that can be accepted. The device for controlling capacity evaluation parameters may generate an evaluation index with the true capacity of the device under test. The device for controlling capacity evaluation parameters may also display the evaluation index to facilitate subsequent judgment by technicians according to the evaluation index.

[0085] The capacity evaluation parameter control method provided by this application enables the capacity evaluation parameter control device to obtain the parameter values of at least one system parameter of the device under test. The capacity evaluation parameter control device can determine the parameter values of at least one evaluation parameter of the device under test based on the parameter values of at least one system parameter of the device under test and a preset tuning algorithm. The capacity evaluation parameter control device can generate a capacity evaluation test case for the device under test according to the parameter values of at least one evaluation parameter, and the capacity evaluation test case is used to evaluate the capacity of the device under test. The capacity evaluation parameter control device can generate a test request based on this capacity evaluation test case. The capacity evaluation parameter control device can send these test requests to the device under test to obtain an evaluation result. The capacity evaluation parameter control device can calculate the true capacity of the device under test based on the statistically obtained evaluation result. In this application, by obtaining the system parameters of the device under test, the generation of personalized evaluation parameters for the device under test is realized, improving the generation efficiency of the evaluation parameters. In addition, this application can also avoid the redundancy of capacity evaluation test cases caused by multiple sets of evaluation parameters by generating capacity evaluation test cases according to the evaluation parameters, improving the evaluation accuracy and evaluation efficiency of the device under test.

[0086] Figure 5 FIG. shows a schematic structural diagram of a capacity evaluation parameter control system provided by an embodiment of this application, as Figure 5 shown, the capacity evaluation parameter control system 10 of this embodiment is used to implement the operations corresponding to the capacity evaluation parameter control device in any of the above method embodiments. The capacity evaluation parameter control system 10 of this embodiment includes:

[0087] An acquisition module 11, configured to acquire the parameter values of at least one system parameter of the device under test.

[0088] A control module 12, configured to determine the parameter values of at least one evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test and a preset tuning algorithm. Generate a capacity evaluation test case for the device under test according to the parameter values of at least one evaluation parameter, and the capacity evaluation test case is used to evaluate the capacity of the device under test.

[0089] In one example, the control module 12 is specifically configured to:

[0090] Determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test.

[0091] Determine the parameter values of each evaluation parameter of the device under test according to the parameter adjustment range of each evaluation parameter and a preset tuning algorithm.

[0092] In one example, the control module 12 is specifically configured to:

[0093] For each evaluation parameter, obtain the calculation model corresponding to the evaluation parameter, and input the parameter value of the system parameter into the calculation model corresponding to the evaluation parameter to calculate and obtain the parameter adjustment range of the evaluation parameter.

[0094] In one example, the control module 12 is specifically configured to:

[0095] Generate a parameter matrix according to the parameter adjustment range of each evaluation parameter.

[0096] Input the parameter matrix into a preset tuning algorithm to obtain the parameter value of each evaluation parameter in the evaluation parameters.

[0097] In one example, the capacity evaluation parameter control system 10 further includes:

[0098] An evaluation module 13 is configured to evaluate the device under test using the capacity evaluation use case corresponding to the device under test to obtain an evaluation result. According to the evaluation result, determine the evaluation index of the device under test, and the evaluation index is used to indicate the true capacity of the device under test.

[0099] In one example, at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

[0100] The capacity evaluation parameter control system 10 provided by the embodiments of the present application can execute the above method embodiments. For the specific implementation principle and technical effects, reference can be made to the above method embodiments, and details are not described herein again.

[0101] Figure 6 Shows a schematic hardware structure diagram of a capacity evaluation parameter control device provided by an embodiment of the present application. As Figure 6 shown, the capacity evaluation parameter control device 20 is used to implement the operations corresponding to the capacity evaluation parameter control device in any of the above method embodiments. The capacity evaluation parameter control device 20 in this embodiment may include: a memory 21, a processor 22, and a communication interface 24.

[0102] The memory 21 is used to store a computer program. The memory 21 may include a high-speed random access memory (Random Access Memory, RAM), and may also include non-volatile storage (Non-Volatile Memory, NVM), such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a disk, or an optical disc, etc.

[0103] The processor 22 is configured to execute the computer program stored in the memory to implement the capacity evaluation parameter control method in the above embodiments. For specific details, reference may be made to the relevant descriptions in the foregoing method embodiments. The processor 22 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in combination with the invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0104] Optionally, the memory 21 may be either independent or integrated with the processor 22.

[0105] When the memory 21 is a device independent of the processor 22, the capacity evaluation parameter control device 20 may further include a bus 23. The bus 23 is used to connect the memory 21 and the processor 22. The bus 23 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0106] The communication interface 24 may be connected to the processor 21 through the bus 23. The communication interface 24 may communicate with the device under test and obtain the parameter values of at least one system parameter of the device under test. The communication interface may also send an evaluation signal to the device under test according to the capacity evaluation use case to implement the evaluation of the device under test.

[0107] The capacity evaluation parameter control device provided in this embodiment can be used to execute the above-mentioned capacity evaluation parameter control method, and its implementation manner and technical effect are similar, which will not be elaborated here in this embodiment.

[0108] This application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided in the above various embodiments.

[0109] Among them, the computer-readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transfer of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the computer-readable storage medium is coupled to the processor, so that the processor can read information from the computer-readable storage medium and write information to the computer-readable storage medium. Of course, the computer-readable storage medium can also be a component of the processor. The processor and the computer-readable storage medium can be located in an Application Specific Integrated Circuits (ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the computer-readable storage medium can also exist as discrete components in a communication device.

[0110] Specifically, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable read-only memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, a magnetic disk or an optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0111] This application also provides a computer program product. The computer program product includes a computer program, and the computer program is stored in a computer-readable storage medium. At least one processor of the device can read the computer program from the computer-readable storage medium, and the at least one processor executes the computer program so that the device implements the methods provided by the above various embodiments.

[0112] An embodiment of this application also provides a chip. The chip includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that a device installed with the chip executes the methods in the above various possible embodiments.

[0113] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or modules can be in electrical, mechanical or other forms.

[0114] Among them, each module can be physically separated, for example, installed at different positions of a device, or installed on different devices, or distributed to multiple network units, or distributed to multiple processors. Each module can also be integrated together, for example, installed in the same device, or integrated in a set of code. Each module can exist in the form of hardware, or can also exist in the form of software, or can also be implemented in the form of software plus hardware. The present application can select some or all of the modules according to actual needs to achieve the purpose of the solution of this embodiment.

[0115] When the integrated modules are implemented in the form of software function modules, they can be stored in a computer-readable storage medium. The above-mentioned software function modules are stored in a storage medium and include several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute some steps of the methods of the various embodiments of the present application.

[0116] It should be understood that although the steps in the flowcharts in the above embodiments are displayed in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless clearly stated in this article, the execution of these steps has no strict order limit, and they can be executed in other orders. Moreover, at least a part of the steps in the figure may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments, and their execution order is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for controlling capacity evaluation parameters, characterized in that The method includes: Obtaining parameter values of at least one system parameter of the device under test; Determining the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test; Generating a parameter matrix according to the parameter adjustment ranges of the respective evaluation parameters; Inputting the parameter matrix into a preset tuning algorithm to obtain the parameter values of each of the evaluation parameters; generating a capacity evaluation case for the device under test according to the parameter values of at least one evaluation parameter, and the capacity evaluation case is used to evaluate the capacity of the device under test.

2. The method according to claim 1, wherein The step of determining the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test specifically includes: For each evaluation parameter, obtaining the calculation model corresponding to the evaluation parameter, and inputting the parameter values of the system parameter into the calculation model corresponding to the evaluation parameter to calculate and obtain the parameter adjustment range of the evaluation parameter.

3. The method according to claim 1 or 2, characterized in that, The method further includes: Evaluating the device under test using the capacity evaluation case corresponding to the device under test to obtain an evaluation result; Determining an evaluation index of the device under test according to the evaluation result, and the evaluation index is used to indicate the true capacity of the device under test.

4. The method according to claim 1 or 2, characterized in that, The at least one system parameter includes at least one of a CPU parameter, a memory parameter, an IO parameter, and a network parameter.

5. A capacity evaluation parameter control system, characterized in that, The system includes: An acquisition module, configured to obtain parameter values of at least one system parameter of the device under test; A control module, configured to determine the parameter adjustment range of each evaluation parameter of the device under test according to the parameter values of at least one system parameter of the device under test; generate a parameter matrix according to the parameter adjustment ranges of the respective evaluation parameters; input the parameter matrix into a preset tuning algorithm to obtain the parameter values of each of the evaluation parameters; generate a capacity evaluation case for the device under test according to the parameter values of at least one evaluation parameter, and the capacity evaluation case is used to evaluate the capacity of the device under test.

6. The system according to claim 5, wherein The system further includes: An evaluation module, configured to evaluate the device under test using the capacity evaluation case corresponding to the device under test to obtain an evaluation result; determine an evaluation index of the device under test according to the evaluation result, and the evaluation index is used to indicate the true capacity of the device under test.

7. A capacity evaluation parameter control device, characterized in that, The device includes: a memory, a processor; The memory is used to store a computer program; the processor is configured to implement the capacity evaluation parameter control method according to any one of claims 1 to 4 according to the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, it is used to implement the capacity evaluation parameter control method according to any one of claims 1 to 4.

9. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the capacity evaluation parameter control method according to any one of claims 1 to 4.

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