Test method and device of mimicry computing system, storage medium and equipment

Abstract

The invention discloses a test method and device for a mimicry computing system, a storage medium and equipment, and the method comprises the steps: determining a to-be-tested mimicry computing system, executing each test task through the to-be-tested mimicry computing system, and according to each network structure formed by computing nodes in the system when the to-be-tested mimicry computing system operates each test task, carrying out the corresponding test task; the method comprises the steps of determining network variability of a to-be-tested mimicry computing system, determining function completeness of the to-be-tested mimicry computing system according to each test task successfully operated by the to-be-tested mimicry computing system, and determining computing performance of the to-be-tested mimicry computing system according to operation performance of the to-be-tested mimicry computing system during operation of each test task. The method can be applied to various mimicry computing systems, provides an objective test method and standard for the comprehensive performance of the mimicry computing system, enables a user to have a clearer and more intuitive understanding of the performance and capability of different mimicry computing systems without actual use, and is convenient for the user to select the mimicry computing system.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a testing method, device, storage medium, and equipment for a mimic computing system. Background Art

[0002] The mimetic computing system is an innovative computing architecture. Compared with traditional high-performance computing clusters, the mimetic computing system is pre-installed with a software and hardware resource library and has a preset task scheduling strategy. It can adapt to computing tasks in a variety of different fields through a set of computing systems, and can achieve more efficient computing through the computing system's own software and hardware structure adjustment capabilities and software and hardware collaborative deployment capabilities.

[0003] Due to the characteristics of the mimetic computing system that can adjust its own structure, the existing high-performance computing cluster performance benchmark tests are difficult to truly reflect the full functional level of a mimetic computing system, and thus it is difficult for users to determine which mimetic computing system product to choose to meet their own research or business needs.

[0004] Therefore, the present invention provides a testing method, device, storage medium, and equipment for a mimic computing system. Summary of the invention

[0005] This specification provides a testing method and device for a mimic computing system to partially solve the above-mentioned problems existing in the prior art.

[0006] This manual adopts the following technical solutions: This specification provides a testing method for a mimic computing system, including: Determine the mimic computing system to be tested; Utilizing the mimetic computing system to be tested to perform various test tasks; Determine the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, determine the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, and determine the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task; A test result of the mimetic computing system to be tested is determined according to the network variability, the functional completeness and the computing performance.

[0007] Optionally, running each test task using the mimic computing system to be tested specifically includes: For any test task, the task description of the test task is input into the simulated computing system to be tested, so that the simulated computing system to be tested can determine the target software resources, target hardware resources and target network structure required to run the test task in the software resource library and hardware resource library of the simulated computing system to be tested, and deploy the target software resources on the target hardware resources to form each computing node, and combine each computing node according to the target network structure to form the system to be tested; The test data corresponding to the test task is input into the system to be tested to execute the test task.

[0008] Optionally, the test tasks specifically include: test tasks of different task types and test tasks of different task computation amounts; Determining the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, specifically includes: Determine the scale of each system to be tested formed by computing nodes in the system when the simulated computing system to be tested runs each test task with different task computational loads, and determine the topology of each network structure formed by computing nodes in the system when the simulated computing system to be tested runs each test task with different task types; The network variability of the mimetic computing system to be tested is determined according to the difference between the scales and the difference between the topological structures.

[0009] Optionally, the test task specifically includes: at least two of an image recognition test task, an encryption and decryption test task, and a web server test task; Determining the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, specifically includes: The functional completeness of the mimetic computing system to be tested is determined according to the number of types of test tasks successfully run by the mimetic computing system to be tested.

[0010] Optionally, determining the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task specifically includes: The computing performance of the simulated computing system to be tested is determined based on at least one of the storage performance when the simulated computing system to be tested runs each test task, the system energy efficiency when the simulated computing system to be tested runs each test task, the acceleration ratio of the simulated computing system to be tested when running each test task, and the network performance when the simulated computing system to be tested runs each test task.

[0011] Optionally, the network variability of the mimetic computing system to be tested is determined according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, and the computing performance of the mimetic computing system to be tested is determined according to the running performance of the mimetic computing system to be tested when running each test task, specifically including: Determine the network variability of the mimetic computing system to be tested for each type of test task according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs the same type of test task, and determine the running performance of the mimetic computing system to be tested when running the same type of test task; The method further comprises: According to the network variability and the computing performance, a test result of the simulated computing system to be tested for each type of test task is determined.

[0012] Optionally, determining a test result of the mimetic computing system to be tested according to the network variability, the functional completeness, and the computing performance specifically includes: A test result of the mimetic computing system to be tested is determined according to the network variability, the functional completeness and the computing performance, and preset test weights corresponding to the network variability, the functional completeness and the computing performance, respectively.

[0013] This specification provides a testing device for a mimic computing system, including: Determine the module and the mimic computing system to be tested; An execution module, using the mimic computing system to be tested to execute various test tasks; A computing module, which determines the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, and determines the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, and determines the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task; An output module determines a test result of the mimetic computing system to be tested according to the network variability, the functional completeness and the computing performance.

[0014] This specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the test method of the mimetic computing system is implemented.

[0015] This specification provides a device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned testing method of the mimetic computing system when executing the program.

[0016] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects: It can be seen from the above method that this method can be applied to various types of mimetic computing systems, and it proposes an objective testing method and standard for the comprehensive performance of mimetic computing systems. It can enable users to have a clearer and more intuitive understanding of the performance and capabilities of different mimetic computing systems without actual use, making it easier for users to choose mimetic computing systems to meet their own research or business needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The illustrative embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation on this specification. In the drawings: Figure 1 A flowchart of a method for testing a mimic computing system in this specification; Figure 2 A schematic diagram of the flow of the simulated computing system performing the test task in this specification; Figure 3 This is a schematic diagram of the display method of the test results in this manual; Figure 4 A schematic diagram of a test device for a mimic computing system provided in this specification; Figure 5 The corresponding Figure 1 Schematic diagram of electronic equipment. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0019] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0020] Figure 1 The flowchart of a method for testing a simulated computing system in this specification is shown in FIG. 1 , and the method for testing a simulated computing system specifically includes the following steps: S100: Determine a mimic computing system to be tested.

[0021] The core idea of ​​the mimetic computing system is to achieve high-efficiency computing through dynamic variable structure and software and hardware collaborative computing. Among them, dynamic variable structure means that the system can dynamically select or generate the best computing structure when executing computing tasks according to the application requirements of the computing tasks to be executed, so as to adapt to different tasks and environmental changes. This dynamic variable structure capability enables the system to adjust its hardware and software resources according to different computing tasks to achieve the best computing performance; and software and hardware collaboration means that in the mimetic computing system, software and hardware are no longer static and fixed combinations, but can adapt and change to each other to form different computing structures. This synergy allows the system to achieve higher energy efficiency ratios through different software and hardware variants while maintaining functional equivalence. These characteristics of the mimetic computing system give it a wide range of application prospects in the fields of high-performance computing, cloud computing, and big data processing. Therefore, the present application provides a test method for a mimetic computing system. The execution subject of this specification may be a test server for testing a mimetic computing system, or other electronic devices that have the ability to connect to the mimetic computing system to be tested, and this specification is not limited here. For the sake of convenience, the following only takes the test server as the execution subject to describe a test method for a mimetic computing system provided in this specification.

[0022] First, a mimic computing system to be tested is determined, and the test server is used to connect to a control server of the mimic computing system to be tested.

[0023] S102: Utilize the mimicking computing system to be tested to perform various test tasks.

[0024] The test server has built-in test programs and data sets corresponding to each test task, and each test task is described and encoded according to the task scheduling strategy of the mimic computing system to determine the task information of the test task, wherein the above-mentioned task information may include the task type of the test task, the data type of the test task, the load change of the test task, etc. Therefore, the test program and data set corresponding to each test task are pre-stored in the test server, which is convenient for the deployment and implementation of subsequent test tasks.

[0025] Furthermore, the simulated computing system to be tested is used to perform various test tasks. For any test task, the task information, test program and data set of the test task can be sent to the control server of the simulated computing system to be tested. The control server can complete the deployment of the test program in the simulated computing system to be tested according to the task information of the test task and its own task scheduling strategy, and use the data set to run the deployed test program to complete the test task.

[0026] S104: Determine the network variability of the mimetic computing system to be tested according to the network structures formed by the computing nodes in the system when the mimetic computing system to be tested runs each test task, determine the functional completeness of the mimetic computing system to be tested according to the test tasks successfully run by the mimetic computing system to be tested, and determine the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task.

[0027] After the control server of the simulated computing system to be tested obtains the task information of any test task, it can determine the operation of the test task according to the task information and its own task scheduling strategy, how to use the software and hardware resources in the software resource library and the hardware resource library to form each computing node, and determine the network structure with which the computing nodes in the system should be connected to perform communication and transmission between the computing nodes. If the network variability of the simulated computing system to be tested is strong, the simulated computing system to be tested can determine a suitable network structure for each test task based on the difference in task information. In the method provided in this specification, the test tasks used to test the simulated computing system to be tested are all different test tasks. Therefore, if the network structure difference of the simulated computing system to be tested for each test task is greater, it can be determined that the network variability of the simulated computing system to be tested is stronger.

[0028] On the other hand, due to its dynamic variable structure and the characteristics of software and hardware collaboration, the mimetic computing system can adapt to the task requirements of a variety of different scenarios. However, in order to execute a test task, the mimetic computing system to be tested still needs to be pre-installed with the software resources and hardware resources required to execute the test task, and its own task scheduling strategy needs to cover the test task, otherwise the deployment of the test program cannot be completed, and the test task cannot be completed. Therefore, the more test tasks the mimetic computing system to be tested successfully runs, the more functional completeness of the mimetic computing system to be tested.

[0029] On the other hand, the mimetic computing system is suitable for high-performance computing due to its own characteristics. Therefore, the computing performance of the mimetic computing system to be tested can be determined based on the running performance of the mimetic computing system to be tested when performing various test tasks.

[0030] Specifically, the above-mentioned network variability, functional completeness and computing performance can be used as test items of the test results, and each test item can be represented by a numerical value. For example, for any test item, the value of the test item can be determined based on the ratio of the actual measured value of the test item of the simulated computing system to be tested and the preset standard value corresponding to the test item.

[0031] For example, the characterization value of the simulated storage bandwidth of the simulated computing system to be tested may be the ratio of the actually measured bandwidth of the simulated computing system to be tested to a preset standard bandwidth.

[0032] In one or more embodiments of the present specification, the computing performance of the simulated computing system to be tested can be determined based on at least one of the storage performance of the simulated computing system to be tested when running each test task, the system energy efficiency of the simulated computing system to be tested when running each test task, the acceleration ratio of the simulated computing system to be tested when running each test task, and the network performance of the simulated computing system to be tested when running each test task.

[0033] Among them, the storage performance of the simulated computing system to be tested may include at least one of the simulated storage bandwidth, the simulated storage response time, and the simulated storage capacity. Similar to the above, the simulated storage bandwidth, the simulated storage response time, the simulated storage capacity, etc. are the test sub-items contained in a test item. For a test sub-item, the test sub-item can be represented by a numerical value, and the value of the test item can be determined according to the ratio of the actual measured value of the simulated computing system to be tested for the test item and the preset standard value corresponding to the test item; the system energy efficiency of the simulated computing system to be tested can be determined by the weighted summation of the energy efficiency index for each test task, wherein the energy efficiency index can be the energy efficiency of the simulated computing system to be tested. The ratio of the energy consumption of a test task to the standard energy consumption of the test task; the acceleration ratio of the simulated computing system to be tested can be determined according to the ratio of the standard time of the simulated computing system to be tested for each test task to the actual time; the network performance can be determined according to at least one of the ratio of the bandwidth of the simulated computing system to be tested for each test task to the standard bandwidth of the test task, the ratio of the delay of the simulated computing system to be tested for each test task to the standard delay of the test task, the ratio of the delay fluctuation of the simulated computing system to be tested for each test task to the standard delay fluctuation of the test task, and the ratio of the packet loss of the simulated computing system to be tested for each test task to the standard packet loss of the test task. It should be noted that for the same test task, for different simulated computing systems to be tested, the standard time of the test task is the same and the standard energy consumption of the test task is the same. When the storage performance of the simulated computing system to be tested includes simulated storage bandwidth, simulated storage response time and simulated storage capacity, the storage performance of the simulated computing system to be tested can be determined by weighted summing the simulated storage bandwidth, simulated storage response time and simulated storage capacity according to preset weights.

[0034] It should also be noted that the standard values ​​corresponding to the above-mentioned test items or sub-test items can be set by the user according to the needs, for example, they can be determined based on the actual measured values ​​of various common high-performance computing clusters.

[0035] S106: Determine a test result of the mimetic computing system to be tested according to the network variability, the functional completeness, and the computing performance.

[0036] After determining the network variability, functional completeness and computing performance of the simulated computing system to be tested, the test result of the simulated computing system to be tested can be determined based on the preset weights and the performance of the simulated computing system to be tested in the above-mentioned three aspects of network variability, functional completeness and computing performance.

[0037] Specifically, the ranking of the level of each test item of the mimetic computing system to be tested among the test items of the known mimetic computing systems can be determined according to the value of each test item, or the value of each test item of the mimetic computing system to be tested can be directly used as the test result of the mimetic computing system to be tested; or the ranking of the comprehensive level of the mimetic computing system to be tested among the known mimetic computing systems can be determined according to the value of each test item, or the weighted average of the test items of the mimetic computing system to be tested can be directly used as the test result of the mimetic computing system to be tested.

[0038] In one or more embodiments of the present specification, the test result of the simulated computing system to be tested is determined based on the network variability, the functional completeness and the computing performance, and the preset test weights corresponding to the network variability, the functional completeness and the computing performance, respectively.

[0039] The test weight can be set according to the actual needs of the user, thereby obtaining a quantitative test result of the mimetic computing system to be tested, objectively indicating the comprehensive capability of the mimetic computing system to be tested.

[0040] like Figure 1 The testing method for a mimetic computing system shown can be applied to various types of mimetic computing systems, and an objective testing method and standard are proposed for the comprehensive performance of the mimetic computing system. It can enable users to have a clearer and more intuitive understanding of the performance and capabilities of different mimetic computing systems without actual use, making it easier for users to choose a mimetic computing system to meet their own research or business needs.

[0041] In addition, in Figure 1 In the step S102 shown, for any test task, the task description of the test task is input into the simulated computing system to be tested, so that the simulated computing system to be tested can determine the target software resources, target hardware resources and target network structure required to run the test task in the software resource library and hardware resource library of the simulated computing system to be tested, and deploy the target software resources on the target hardware resources to constitute each computing node, combine each computing node according to the target network structure to form the system to be tested, and input the test data corresponding to the test task into the system to be tested to execute the test task.

[0042] The process is as follows Figure 2 As shown, firstly, step S200 is performed: the test system inputs the test task into the mimic computing system to be tested; After the mimetic computing system receives the test, step S202 is performed: the mimetic computing system to be tested determines the target software resources, target hardware resources, and target network structure required to run the test task in the software resource library and hardware resource library of the mimetic computing system to be tested; After all the determinations are completed, step S204 is executed: the mimic computing system to be tested deploys the target software resources on the target hardware resources to constitute each computing node, and combines each computing node according to the target network structure to form the system to be tested; Then, step S206 is executed: the test system inputs the test data corresponding to the test task into the system to be tested; Finally, step S208 is executed: the mimic computing system to be tested executes the test task.

[0043] In one or more embodiments of the present specification, step S206 may be advanced to be performed simultaneously with step S200 , and step S208 needs to be performed after step S204 .

[0044] Specifically, the software resource library may include a computing core library, an application image library, a network structure library, etc.; the hardware resource library may include a computing power resource library composed of devices that provide computing power, a storage resource library composed of devices that provide storage capacity, a communication resource library composed of devices that provide communication routing functions, etc. Among them, the computing core library may include packaged and reusable computing functions for applications in different scenarios, the application image library may include the deployment environment information required for applications in different scenarios, and the network structure library may include computing node communication structures for different scenarios.

[0045] In addition, the test tasks specifically include: test tasks of different task types, test tasks of different task computation amounts; Figure 1 In the step S104 shown, the scale of each system under test composed of computing nodes in the system is determined when the simulated computing system under test runs each test task with different task computational load, and the topological structure of each network structure composed of computing nodes in the system is determined when the simulated computing system under test runs each test task with different task types. Based on the difference between the scales and the difference between the topological structures, the network variability of the simulated computing system under test is determined.

[0046] It is easy to know that different test tasks with different computing amounts and task types have different requirements for the computing amount and communication capabilities of the computing system. For example, model training tasks have higher requirements for computing power and often require a one-to-one connection between computing nodes, while encryption and decryption tasks also have higher requirements for computing power, but may require a one-to-many connection between computing nodes. Therefore, for different types of test tasks, the mimetic computing system should reasonably adjust its own network structure according to the test tasks to improve computing efficiency, so as to give full play to its advantages over traditional high-performance computing clusters.

[0047] Among them, the scale of the network structure can be determined according to at least one of the total computing power or the number of nodes of the system to be tested for a test task; the node scale adjustment capability of the system to be tested of the simulated computing system to be tested for a test task can be determined according to the difference between the scales of different systems to be tested composed of the simulated computing system to be tested for test tasks with different computing amounts, the more the difference between the scales adapts to the difference in computing amounts between the test tasks, the stronger the node scale adjustment capability of the simulated computing system to be tested; kernel methods can be used to determine the differences between topological structures.

[0048] In one or more embodiments of the present specification, when the simulated computing system to be tested runs the same test task, the scale of each system to be tested constituted by the computing nodes in the system is determined when receiving test data of different data amounts, and when the simulated computing system to be tested runs each test task of different task types, the topological structure of each network structure constituted by the computing nodes in the system is determined, and based on the differences between the scales and the differences between the topological structures, the network variability of the simulated computing system to be tested is determined.

[0049] The process of the tested mimetic computing system running a test task can be a process of continuously receiving data sent by a test server and processing the data. The frequency of data sending by the test server can be dynamically changed. Accordingly, in order to improve computing efficiency, the scale of the system to be tested composed of the mimetic computing system to be tested should also be changed accordingly. Therefore, the node scale adjustment capability of the system to be tested of the mimetic computing system to be tested for a test task can be determined according to the difference between the scales of different systems to be tested composed of the mimetic computing system to be tested with different data sending frequencies for the same test task. The more the difference between the scales adapts to the difference in different data sending frequencies, the stronger the network variability and the node scale adjustment capability of the mimetic computing system to be tested.

[0050] On the other hand, the test tasks specifically include: at least two of an image recognition test task, an encryption and decryption test task, and a web server test task; Figure 1 In step S104 shown, the functional completeness of the mimic computing system to be tested is determined according to the number of types of test tasks successfully run by the mimic computing system to be tested.

[0051] Depending on the differences in the application scenarios faced, the types of test tasks may include but are not limited to image recognition test tasks, encryption and decryption test tasks, and web server test tasks. The software resource library and hardware resource library of the mimetic computing system to be tested need to prepare corresponding software and hardware resources to enable the mimetic computing system to be tested to adapt to different application scenarios.

[0052] In one or more embodiments of the present specification, the acceleration ratio of the simulated computing system to be tested running each test task may include the acceleration ratio of each type of test task of the simulated computing system to be tested, and the above-mentioned type may be one of an image recognition test task, an encryption and decryption test task, and a web server test task. The acceleration ratio of a type of test task can be determined based on the average of the acceleration ratios of each test task of the same type running by the simulated computing system to be tested.

[0053] In addition, in Figure 1 In step S104, the network variability of the simulated computing system to be tested for each type of test task is determined according to each network structure formed by computing nodes in the system when the simulated computing system to be tested runs the same type of test task, and the network variability of the simulated computing system to be tested for each type of test task is determined according to the running performance of the simulated computing system to be tested when running the same type of test task. Figure 1 After step S104 shown, the test results of the simulated computing system to be tested for each type of test task are determined according to the network variability and the computing performance.

[0054] The method provided in this specification can also determine the single-dimensional test results of the simulated computing system to be tested for each application scenario, providing more fine-grained reference materials for the user's selection. Among them, one application scenario can correspond to one type of test task.

[0055] For each application scenario, Figure 3 The test result diagram shown represents the test result of the simulated computing system to be tested. The network variability reference value and the computing performance reference value can be determined based on the statistical values ​​of the simulated computing system tested in the application scenario. Specifically, statistical values ​​such as the mean or median can be selected according to the needs of the user. The solid circles in the diagram can represent the statistical values ​​of each tested simulated computing system, and the hollow circles can represent the statistical values ​​of the simulated computing system to be tested, which can more intuitively represent the test results of the simulated computing system to be tested.

[0056] The above is the XX method provided by one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding test device for the mimic computing system, such as Figure 4 shown.

[0057] Figure 4 A schematic diagram of a test device for a mimic computing system provided in this specification specifically includes: A determination module 400 determines a mimic computing system to be tested; An execution module 402 executes each test task using the mimic computing system to be tested; The computing module 404 determines the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, determines the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, and determines the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task; The output module 406 determines the test result of the simulated computing system to be tested according to the network variability, the functional completeness and the computing performance.

[0058] Optionally, the execution module 402 is specifically used to: for any test task, input the task description of the test task into the simulated computing system to be tested, so that the simulated computing system to be tested can determine the target software resources, target hardware resources and target network structure required to run the test task in the software resource library and hardware resource library of the simulated computing system to be tested, and deploy the target software resources on the target hardware resources to constitute each computing node, combine the computing nodes according to the target network structure to form the system to be tested, and input the test data corresponding to the test task into the system to be tested to execute the test task.

[0059] Optionally, the test tasks specifically include: test tasks of different task types and test tasks of different task computation amounts; The computing module 404 is specifically used to: determine the scale of each system under test composed of computing nodes in the system when the simulated computing system under test runs each test task with different task computational load, and determine the topological structure of each network structure composed of computing nodes in the system when the simulated computing system under test runs each test task with different task types, and determine the network variability of the simulated computing system under test based on the difference between the scales and the difference between the topological structures.

[0060] Optionally, the test task specifically includes: at least two of an image recognition test task, an encryption and decryption test task, and a web server test task; The calculation module 404 is specifically configured to determine the functional completeness of the mimic computing system to be tested according to the number of types of test tasks successfully run by the mimic computing system to be tested.

[0061] Optionally, the computing module 404 is specifically used to determine the computing performance of the simulated computing system to be tested based on at least one of the storage performance of the simulated computing system to be tested when running each test task, the system energy efficiency of the simulated computing system to be tested when running each test task, the acceleration ratio of the simulated computing system to be tested when running each test task, and the network performance of the simulated computing system to be tested when running each test task.

[0062] Optionally, the computing module 404 is specifically used to: determine the network variability of the mimetic computing system to be tested for each type of test task according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs the same type of test task, and, according to the running performance of the mimetic computing system to be tested when running the same type of test task; The output module 406 is further used to determine the test results of the simulated computing system to be tested for each type of test task according to the network variability and the computing performance.

[0063] Optionally, the output module 406 is specifically used to determine the test result of the simulated computing system to be tested according to the network variability, the functional completeness and the computing performance, and the preset test weights corresponding to the network variability, the functional completeness and the computing performance, respectively.

[0064] This specification also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 A testing method for a mimetic computing system is provided.

[0065] This manual also provides Figure 5 The schematic structure diagram of the electronic device shown in FIG. Figure 5 As mentioned above, at the hardware level, the test equipment of the virtual computing system includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and of course may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 Of course, in addition to the software implementation, this specification does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0066] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with hardware entity modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0067] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0068] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0069] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0070] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0072] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0074] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0075] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0076] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0077] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0078] It should be understood by those skilled in the art that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0080] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0081] The above description is only an embodiment of this specification and is not intended to limit this specification. For those skilled in the art, this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this specification should be included in the scope of the claims of this application.

Claims

1. A method for testing a mimic computing system, characterized in that: The method comprises: Determine the mimic computing system to be tested; Utilizing the mimetic computing system to be tested to perform various test tasks; Determine the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, determine the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, and determine the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task; A test result of the mimetic computing system to be tested is determined according to the network variability, the functional completeness and the computing performance.

2. The method according to claim 1, characterized in that The test tasks are run by using the mimic computing system to be tested, specifically including: For any test task, the task description of the test task is input into the simulated computing system to be tested, so that the simulated computing system to be tested can determine the target software resources, target hardware resources and target network structure required to run the test task in the software resource library and hardware resource library of the simulated computing system to be tested, and deploy the target software resources on the target hardware resources to form each computing node, and combine each computing node according to the target network structure to form the system to be tested; The test data corresponding to the test task is input into the system to be tested to execute the test task.

3. The method according to claim 1, characterized in that The test tasks specifically include: test tasks of different task types and test tasks of different task computation amounts; Determining the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, specifically includes: Determine the scale of each system to be tested formed by computing nodes in the system when the simulated computing system to be tested runs each test task with different task computational loads, and determine the topology of each network structure formed by computing nodes in the system when the simulated computing system to be tested runs each test task with different task types; The network variability of the mimetic computing system to be tested is determined according to the difference between the scales and the difference between the topological structures.

4. The method according to claim 1, characterized in that The test tasks specifically include: at least two of an image recognition test task, an encryption and decryption test task, and a web server test task; Determining the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, specifically includes: The functional completeness of the mimetic computing system to be tested is determined according to the number of types of test tasks successfully run by the mimetic computing system to be tested.

5. The method according to claim 1, characterized in that Determining the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task specifically includes: The computing performance of the simulated computing system to be tested is determined based on at least one of the storage performance when the simulated computing system to be tested runs each test task, the system energy efficiency when the simulated computing system to be tested runs each test task, the acceleration ratio of the simulated computing system to be tested when running each test task, and the network performance when the simulated computing system to be tested runs each test task.

6. The method according to claim 3, characterized in that Determining the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, and determining the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task, specifically including: Determine the network variability of the mimetic computing system to be tested for each type of test task according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs the same type of test task, and determine the running performance of the mimetic computing system to be tested when running the same type of test task; The method further comprises: According to the network variability and the computing performance, a test result of the simulated computing system to be tested for each type of test task is determined.

7. The method according to claim 1, characterized in that Determining a test result of the mimetic computing system to be tested according to the network variability, the functional completeness, and the computing performance, specifically includes: A test result of the mimetic computing system to be tested is determined according to the network variability, the functional completeness and the computing performance, and preset test weights corresponding to the network variability, the functional completeness and the computing performance, respectively.

8. A testing device for a mimic computing system, characterized in that: include: Determine the module and the mimic computing system to be tested; An execution module, using the mimic computing system to be tested to execute various test tasks; A computing module, which determines the network variability of the mimetic computing system to be tested according to each network structure formed by computing nodes in the system when the mimetic computing system to be tested runs each test task, and determines the functional completeness of the mimetic computing system to be tested according to each test task successfully run by the mimetic computing system to be tested, and determines the computing performance of the mimetic computing system to be tested according to the running performance of the mimetic computing system to be tested when running each test task; An output module determines a test result of the mimetic computing system to be tested according to the network variability, the functional completeness and the computing performance.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of claims 1 to 7 is implemented.

10. A device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method described in any one of claims 1 to 7 is implemented.

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