CAE solution performance optimization system and method

Abstract

The invention belongs to the technical field of cloud computing, and particularly discloses a CAE solution performance optimization system and method.The system comprises a CAE local end and a server cluster of the cloud end; the local end deploys a cloud computing plug-in, the server cluster deploys a cloud computing service, and the cloud computing plug-in is used for automatically shielding a CAE local solving operation instruction when a user uses a local solving unit to solve at the local end; uploading the calculation solving work directory to a cloud end, enabling the cloud end to execute the solving operation instruction to obtain a cloud end solving result, receiving the solving result sent by the cloud end, and downloading the solving result to a local end; the cloud computing service is used for providing a cloud computing API interface and a cloud computing supporting service to the outside so as to realize development of a CAE end cloud computing plug-in, and realizing cloud computing and interaction between a local end and a cloud end by calling the cloud computing API interface. According to the invention, the solution efficiency of the CAE can be improved.

Description

Technical Field

[0001] The present application belongs to the field of cloud computing technology, and more specifically, to a CAE solution performance optimization system and method. Background Art

[0002] In recent years, due to information security and independent controllability, the domestic demand for domestic industrial software has been growing. As an important branch of industrial software, CAE is also accelerating its localization substitution process. With the increase in the localization rate, CAE needs to compete with international brands in terms of solution performance to meet the domestic manufacturing industry's demand for high-performance CAE.

[0003] As an open source CAE, FastCAE is committed to promoting the openness and flexibility of the CAE ecosystem. By providing a solver integration platform, CAE can support users to easily integrate self-developed solvers and third-party solvers, breaking the limitations of traditional CAE in solver selection and providing users with more diverse choices. It can meet the solution application requirements in different fields and different physical fields. CAE's solver integration platform not only supports the integration of third-party solvers, but also supports the integration of user-developed solvers. Through the tools and services provided by the platform, users can easily encapsulate self-developed solvers into standard CAE modules for rapid productization.

[0004] However, the solving performance of CAE solvers is generally limited by factors such as solving algorithms and models, solver memory management and computational scheduling, parallel computing, and hardware performance. It is difficult to achieve a leapfrog growth in solving performance. Due to the limitations of local hardware performance, the solving efficiency of CAE is low.

[0005] Therefore, how to break through the limitations of local hardware performance and thereby improve the efficiency of CAE solutions is a technical problem that urgently needs to be solved. Summary of the invention

[0006] In view of the defects of the prior art, the purpose of this application is to provide a CAE solution performance optimization system and method, aiming to solve the problem of low CAE solution efficiency.

[0007] In a first aspect, the present application provides a CAE performance optimization system, including a CAE local terminal and a server cluster in the cloud; the local terminal deploys a cloud computing plug-in, and the server cluster deploys a cloud computing service:

[0008] The cloud computing plug-in is used to automatically shield CAE local solution operation instructions when the user uses the local solution unit to solve the problem on the local side; upload the calculation solution working directory to the cloud, so that the cloud executes the solution operation instructions to obtain the cloud solution result, and receive the solution result sent by the cloud to the local side for download;

[0009] The cloud computing service is used to realize the development of CAE-side cloud computing plug-ins by providing cloud computing API interfaces and cloud computing supporting services to the outside world, and to realize cloud computing and interaction between the local side and the cloud by calling the cloud computing API interfaces.

[0010] The CAE-side cloud computing plug-in of the present application is deployed on CAE, which can automatically shield CAE local solution operations and realize cloud computing, that is, after detecting the CAE solution signal and the CAE cloud computing enable signal, it will skip the local solution and perform cloud computing operations instead, such as uploading the local solution working directory to the cloud, cloud solution, and downloading the cloud solution results; cloud computing services are deployed on server clusters to provide cloud computing API interfaces and cloud computing supporting services to the outside world. CAE users can quickly develop CAE-side cloud computing plug-ins by calling the external API interface of cloud computing services, and realize operations such as uploading the solution working directory to the cloud, cloud solution, and downloading the cloud solution results on the CAE side. The present application realizes compatibility with existing CAE local solution units, that is, after adding the CAE-side cloud computing plug-in to CAE, the existing CAE local solution units can realize cloud computing solutions without any operation; at the same time, the present application breaks through the limitations of local hardware performance, and uses high-performance server clusters to improve the solver's single-core CPU performance and the upper limit of the number of parallel solution CPU cores, greatly improving the CAE solution efficiency.

[0011] Optionally, the cloud computing plug-in integrates cloud computing functions into CAE and is compatible with the local solution unit of CAE;

[0012] The cloud computing plug-in includes an enabling signal monitoring unit, a cloud computing unit, and an output unit;

[0013] An enabling signal monitoring unit, used to determine whether the user enables cloud computing after the local solving unit completes solving and outputs a solution file, and to disable the local solving unit and enable the cloud computing unit when the determination result is yes;

[0014] The cloud computing unit interacts with the cloud through an API interface to upload the solution working directory to the cloud, perform solution in the cloud, and download the solution results;

[0015] The output unit is used to uniformly output the solution results of the local solution unit and the calculation results of the cloud computing unit.

[0016] Optionally, the local end includes a pre-processing module, a solution drive and process control module, a local solution module and a post-processing module;

[0017] The pre-processing module is used to draw the geometric model, divide the mesh, set the working parameters and solver, and determine the solution model information;

[0018] The solution drive and process control module is used to call the solver to perform the solution task;

[0019] The local solution module is used to output the solution model information as a solution file, store the solution file in a local solution working directory, and send an enable signal to the cloud computing plug-in.

[0020] Optionally, the enable signal monitoring unit is further used to, when the judgment result is no, use the local solution unit to perform local solution, output the result file of the local solution, and convert the result file into a specific format file of tabular data or VTK data;

[0021] The local end also includes a post-processing module;

[0022] The post-processing module is used to display the specific format file output from the cloud in two-dimensional or three-dimensional images.

[0023] Optionally, the cloud computing service includes an API component, an access control component, a security component, a data management component, and a node management component;

[0024] The API component is used to provide an interactive interface between external applications and cloud computing services, call cloud computing resources and submit computing tasks according to user input, and obtain computing results;

[0025] The access control component is used to manage and authorize users' access rights to cloud computing services to implement user registration, login, permission allocation and identity authentication;

[0026] The security component is used to provide security for CAE cloud computing services, prevent illegal access, data leakage and malicious attacks, and provide data encryption, identity authentication and firewall;

[0027] The data management component is used to manage and store data in the cloud computing service;

[0028] The node management component is used to manage and schedule computing nodes in cloud computing services to achieve dynamic allocation and load balancing of computing resources.

[0029] Optionally, the API component includes at least one of: a user registration interface, a user login interface, a file upload interface, a file download interface, a file list acquisition interface, a computing task submission interface, a computing task status query interface, and a computing task cancellation interface.

[0030] The present application also provides a CAE solution performance optimization method, which is applied to a CAE software system, wherein the software system includes a local end and a server cluster in the cloud; a cloud computing plug-in is deployed on the local end, and a cloud computing service is deployed on the server cluster, and the method includes:

[0031] When the user uses the local solution unit to solve on the local side, the CAE local solution operation instructions are automatically shielded by the cloud computing plug-in;

[0032] Upload the calculation and solution working directory to the cloud, execute the solution operation instructions through the cloud, and obtain the cloud solution results;

[0033] Send the cloud solution results to the local terminal for download;

[0034] The cloud computing service provides cloud computing API interfaces and cloud computing supporting services to realize the development of CAE-side cloud computing plug-ins, and realizes cloud computing by calling the cloud computing API.

[0035] Optionally, it also includes:

[0036] Receive user requests through the API component and verify user permissions through the security component;

[0037] When the verification is passed, the user request is pushed to the access control component, which identifies the cloud upload operation and sends a cloud upload request to the data management component;

[0038] Uploaded files are stored through the data storage layer of the data management component.

[0039] In a third aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0041] In a fifth aspect, the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0042] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0043] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art:

[0044] (1) The CAE-side cloud computing plug-in of the present application is deployed on CAE, which can automatically shield CAE local solution operations and realize cloud computing, that is, after detecting the CAE solution signal and the CAE cloud computing enable signal, it will skip the local solution and perform cloud computing operations instead, such as uploading the local solution working directory to the cloud, cloud solution, and downloading the cloud solution results; cloud computing services are deployed on server clusters to provide cloud computing API interfaces and cloud computing supporting services to the outside world. CAE users can quickly realize CAE-side cloud computing plug-in development by calling the cloud computing service external API interface, and realize operations such as uploading the solution working directory to the cloud, cloud solution, and downloading the cloud solution results on the CAE side. The present application realizes compatibility with existing CAE local solution units, that is, after CAE adds the CAE-side cloud computing plug-in, the existing CAE local solution unit can realize cloud computing solution without any operation; at the same time, the present application breaks through the limitations of local hardware performance, and uses high-performance server clusters to improve the solver's single-core CPU performance and the upper limit of the number of parallel solution CPU cores, greatly improving the CAE solution efficiency.

[0045] (2) Local computing resources can be effectively utilized, avoiding computing bottlenecks caused by insufficient local hardware. Users do not need to update or expand local hardware.

[0046] (3) The design of the cloud computing plug-in of the present application can automatically identify and block local solution operation instructions, thereby simplifying user operations and reducing the errors or confusion that users may encounter when switching computing environments.

[0047] (4) Through the API interface provided by the cloud service, the cloud computing plug-in on the CAE side can be flexibly adjusted and expanded to meet the changes in different user needs and computing tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a block diagram of the cloud computing service structure provided by the embodiment of the present application;

[0049] Figure 2 It is a CAE cloud computing plug-in design flow chart provided in an embodiment of the present application;

[0050] Figure 3 It is a CAE local solution mode diagram provided in an embodiment of the present application;

[0051] Figure 4 It is a CAE cloud solution mode diagram provided in an embodiment of the present application;

[0052] Figure 5It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] The term "and / or" in this article is a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The symbol " / " in this article indicates that the associated objects are in an or relationship, for example, A / B means A or B.

[0055] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first response message and a second response message are used to distinguish different response messages rather than to describe a specific order of the response messages.

[0056] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0057] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. For example, multiple processing units refer to two or more processing units, etc.; multiple elements refer to two or more elements, etc.

[0058] Next, the technical solutions provided in the embodiments of the present application are introduced.

[0059] The present application provides a CAE solution performance optimization system, including a CAE local end and a server cluster in the cloud; the local end deploys a cloud computing plug-in, and the server cluster deploys a cloud computing service:

[0060] The cloud computing plug-in is used to automatically shield CAE local solution operation instructions when the user uses the local solution unit to solve the problem on the local side; upload the calculation solution working directory to the cloud, so that the cloud executes the solution operation instructions to obtain the cloud solution result, and receive the solution result sent by the cloud to the local side for download;

[0061] The cloud computing service is used to realize the development of CAE-side cloud computing plug-ins by providing cloud computing API interfaces and cloud computing supporting services to the outside world, and to realize cloud computing and interaction between the local side and the cloud by calling the cloud computing API interfaces.

[0062] Specifically, the system architecture of the present application includes a CAE local end and a cloud server cluster.

[0063] CAE local end:

[0064] A cloud computing plug-in will be deployed on the local side as a bridge between the user and the cloud server cluster. When the user uses the local solver unit to simulate or calculate on the local machine, the plug-in will automatically monitor the current computing task and dynamically adjust according to the task requirements.

[0065] When a user starts a computing task, the cloud computing plug-in will determine the complexity and resource requirements of the task, and then automatically block all local solution operation instructions to avoid computing failures due to insufficient resources.

[0066] Cloud server cluster:

[0067] The cloud cluster consists of multiple high-performance computing servers that can handle multiple solution tasks in parallel. These servers are equipped with hardware and software environments optimized for CAE tasks, and can quickly execute computing tasks and return results. The cloud computing service will provide an API interface for local cloud computing plug-ins to call to upload, execute, and return results of computing tasks.

[0068] The workflow of this system is as follows:

[0069] First, task identification and upload. The user uses the solver to define the computing task on the local side. Second, once the working directory is uploaded, the cloud server cluster will start to execute the solving operation according to the received computing task instructions. This process includes scheduling computing resources, executing the solving algorithm and performing the required post-processing. After the solving process is completed, the cloud will generate the solution results and feed them back to the local side. The cloud computing plug-in is responsible for receiving the results and downloading them to the user's local computer for subsequent analysis and use.

[0070] It should be noted that the cloud computing service in this embodiment will provide a set of API interfaces to allow the CAE local plug-in to interact with the cloud server. These API interfaces will cover the following functions: receiving the solution task uploaded by the local end and returning the task processing status. Allowing the local end to query the execution status of the solution task in the cloud. Providing a safe and effective way for users to download the cloud computing results.

[0071] The CAE solution performance optimization system of this application uses cloud computing technology to provide CAE users with an efficient and reliable solution. Through automatic monitoring, resource optimization and cloud computing, the system can significantly improve the performance and efficiency of CAE solutions.

[0072] The embodiment of the present application transfers the computing tasks to the cloud. The cloud server cluster is usually equipped with a more powerful CPU and multi-core processing power, which can provide higher computing performance than general local computers. By utilizing multiple CPU cores and nodes in the cloud, multiple computing tasks can be processed in parallel or multiple cores can be allocated in the same task for parallel computing, which significantly improves the overall computing efficiency. After the cloud solution is completed, the results can be quickly sent to the local end to ensure that the user can obtain the calculation results in time for subsequent analysis and decision-making, thereby improving overall work efficiency. Through this application, users can use the powerful computing power of the cloud to break through the limitations of local hardware and effectively improve the overall efficiency of CAE (computer-aided engineering) solutions.

[0073] Optionally, the cloud computing plug-in integrates cloud computing functions into CAE and is compatible with the local solution unit of CAE;

[0074] The cloud computing plug-in includes an enabling signal monitoring unit, a cloud computing unit, and an output unit;

[0075] An enabling signal monitoring unit, used to determine whether the user enables cloud computing after the local solving unit completes solving and outputs a solution file, and to disable the local solving unit and enable the cloud computing unit when the determination result is yes;

[0076] The cloud computing unit interacts with the cloud through an API interface to upload the solution working directory to the cloud, perform solution in the cloud, and download the solution results;

[0077] The output unit is used to uniformly output the solution results of the local solution unit and the calculation results of the cloud computing unit.

[0078] Specifically, the cloud computing plug-in in this embodiment serves as an integrated module responsible for coordinating the interaction between the local computing environment and cloud resources so as to offload the computing load to the cloud for processing when necessary.

[0079] The enable signal monitoring unit is responsible for monitoring the status of the local solution unit and whether the user has enabled the cloud computing function. When the local solution unit completes the calculation and outputs the solution file, this module will determine whether the user has selected cloud computing as the solution method.

[0080] If the user has enabled cloud computing, the module will shield the output operations of the local solution unit to avoid repeated calculations and resource waste, and activate the cloud computing unit at the same time, thereby performing more efficient computing resource scheduling.

[0081] If the user does not enable this function, the local solution unit will continue to be used for calculation, maintaining the traditional solution process.

[0082] The cloud solver is responsible for reading the uploaded solution files on the cloud platform and performing calculations based on them. It automatically obtains the solution files in the working directory as calculation input based on the cloud environment. Through the API interface, it interacts with the local user interface in real time and provides users with important information about the calculation process, including the progress of the solution and the current status. It allows users to understand the real-time status of the cloud solution and effectively manage their calculation tasks.

[0083] The process is as follows: the cloud solver will automatically obtain the solution file in the working directory as input and start solving; at the same time, during the execution of the cloud solver, the solver solution process information and solution progress can be fed back to the local UI interface in real time through the API interface; after the cloud solver completes the solution, the result file is obtained, and a solution completion signal is sent to the cloud computing unit of the CAE cloud computing plug-in.

[0084] The cloud computing unit is responsible for comprehensive API interface interaction with the cloud, supporting the uploading of tasks, the execution of cloud solutions, and the downloading of solution results.

[0085] Upload the local solution file to the cloud to ensure that the cloud solver can successfully obtain and process the required input data. After the cloud solution is completed, obtain the solution results through the API and download the results to the local computer for subsequent analysis and use.

[0086] The output unit integrates the calculation results generated by the cloud solver and the cloud computing unit and provides a unified output format.

[0087] The overall process is described as follows:

[0088] When the user performs calculations in the local solver unit, the plug-in starts monitoring the user's settings.

[0089] After the solution is completed, the monitoring module determines whether the user has enabled cloud computing. If enabled, the local solution unit is disabled and the cloud computing unit is activated. If not enabled, the local solution unit is continued to be used to output the results.

[0090] If the cloud computing unit is activated, the solution files in the working directory are automatically uploaded to the cloud and the cloud solver is started.

[0091] The cloud-based solver performs calculations based on the input files and provides real-time feedback of the calculation progress to the user through the API.

[0092] After the solution is completed, the cloud computing unit downloads the results to the local computer and uniformly formats and displays them through the output unit.

[0093] The embodiment of the present application integrates cloud computing functions in a modular way, achieving efficient collaboration between local solution units and cloud solution resources. Through intelligent monitoring and dynamic language, users can fully utilize the advantages of cloud computing and significantly improve solution efficiency.

[0094] Optionally, the local end includes a pre-processing module, a solution drive and process control module, a local solution module and a post-processing module;

[0095] The pre-processing module is used to draw the geometric model, divide the mesh, set the working parameters and solver, and determine the solution model information;

[0096] The solution drive and process control module is used to call the solver to perform the solution task;

[0097] The local solution module is used to output the solution model information as a solution file, store the solution file in a local solution working directory, and send an enable signal to the cloud computing plug-in.

[0098] Optionally, the enable signal monitoring unit is further used to, when the judgment result is no, use the local solution unit to perform local solution, output the result file of the local solution, and convert the result file into a specific format file of tabular data or VTK data;

[0099] The local end also includes a post-processing module;

[0100] The post-processing module is used to display the specific format file output from the cloud in two-dimensional or three-dimensional images.

[0101] Specifically, the pre-processing module is responsible for building the model required for the calculation, including geometric modeling and solution settings. Geometric model drawing: The user draws the required geometric model through the graphical interface and defines the shape and size of the analysis object. Meshing: Discretize the geometric model and generate a computational mesh suitable for solver processing to improve solution accuracy and efficiency. Working condition parameter setting: The user defines various working conditions (such as boundary conditions, loads, material properties, etc.) to ensure that the model can reflect the actual situation. Solver settings: According to the characteristics of the model and working conditions, select appropriate solver configuration parameters to optimize calculation performance and result quality.

[0102] The solution drive and process control module is responsible for controlling the solution process and coordinating the execution of the solver.

[0103] According to the solution model information provided by the pre-processing module, the local solution unit can be automatically called for calculation. The solution process is monitored to ensure that the solution task proceeds smoothly according to the predetermined steps and handle abnormal situations in the solution process.

[0104] This module enables the solution process to be managed efficiently and orderly to reduce the complexity of user operations.

[0105] The core function of the local solution unit is to convert the solution model information generated by the pre-processing module into a solution file and perform the calculation task. According to the set model and working condition parameters, a solution file containing all necessary information is generated for use by the solver. The generated solution file is saved in the local solution working directory for subsequent viewing and management. After completing the output of the solution file, the module sends an enable signal to the cloud computing plug-in to determine whether cloud computing resources need to be used in the future.

[0106] The post-processing module is responsible for analyzing and visualizing the solution results to help users understand and apply the calculation results.

[0107] The overall process is described as follows:

[0108] The user creates a geometric model and sets analysis parameters in the pre-processing module to complete the construction and configuration of the model. After completing the pre-processing, the solution drive and process control module calls the local solution unit to perform the solution task. The local solution unit generates the solution file and stores it in the local working directory. At this time, an enable signal is sent to the cloud computing plug-in at the same time. The local solution unit performs the corresponding calculation according to the input file and outputs the result. The post-processing module reads and analyzes the solution results and displays them to the user for further use and analysis.

[0109] The embodiment of the present application provides necessary support for each stage of the solution process by reasonably dividing the local functional modules, thereby improving computing efficiency and user experience. The system can not only meet the user's demand for local solution, but also facilitate the use of cloud computing resources when needed, showing strong flexibility and adaptability.

[0110] Optionally, the cloud computing service includes an API component, an access control component, a security component, a data management component, and a node management component;

[0111] The API component is used to provide an interactive interface between external applications and cloud computing services, call cloud computing resources and submit computing tasks according to user input, and obtain computing results;

[0112] The access control component is used to manage and authorize users' access rights to cloud computing services to implement user registration, login, permission allocation and identity authentication;

[0113] The security component is used to provide security for CAE cloud computing services, prevent illegal access, data leakage and malicious attacks, and provide data encryption, identity authentication and firewall;

[0114] The data management component is used to manage and store data in the cloud computing service;

[0115] The node management component is used to manage and schedule computing nodes in cloud computing services to achieve dynamic allocation and load balancing of computing resources.

[0116] like Figure 1 As shown in the figure, cloud computing services include API components, access control components, security components, data management components, and node management components. Taking the client calling the upload cloud interface as an example, the API component receives the user request, the security component performs user permission verification, and pushes the user request to the access control component after passing. The access control component identifies the upload cloud operation and sends the upload cloud request to the data management component. Finally, the data storage layer completes the storage of the uploaded file.

[0117] API component: The API component is the core interface part of the CAE cloud computing service. It is responsible for providing an interactive interface between external applications and cloud computing services, allowing users to call cloud computing resources programmatically, submit computing tasks, and obtain computing results.

[0118] Access control component: The access control component is responsible for managing and authorizing users' access rights to CAE cloud computing services, and implementing user registration, login, permission allocation, and identity authentication.

[0119] Security component: The security component is the security guarantee of CAE cloud computing services. It is responsible for preventing illegal access, data leakage and malicious attacks, and provides security measures such as data encryption, identity authentication, and firewalls.

[0120] Data management component: The data management component is responsible for managing and storing data in CAE cloud computing services, including user data, computing tasks and results.

[0121] Node management component: The node management component is responsible for managing and scheduling computing nodes in CAE cloud computing services to achieve dynamic allocation and load balancing of computing resources.

[0122] Optionally, the API component includes at least one of: a user registration interface, a user login interface, a file upload interface, a file download interface, a file list acquisition interface, a computing task submission interface, a computing task status query interface, and a computing task cancellation interface.

[0123] Specifically, the embodiment of the present application designs a set of cloud computing service API interfaces. The cloud computing service API interface design includes interface name, interface description, interface request parameters, and interface response parameters. The cloud computing service provides standard API calls to the outside world to achieve rapid development of cloud computing clients. As shown in Table 1, the cloud computing service API interface types include: user registration, user login, file upload, file download, file list acquisition, submitting computing tasks, querying computing task status, and canceling computing tasks.

[0124] Table 1: Cloud computing service API interface design table

[0125]

[0126]

[0127] The present application also provides a CAE solution performance optimization method, which is applied to a CAE software system, wherein the software system includes a local end and a server cluster in the cloud; a cloud computing plug-in is deployed on the local end, and a cloud computing service is deployed on the server cluster, and the method includes:

[0128] When the user uses the local solution unit to solve on the local side, the CAE local solution operation instructions are automatically shielded by the cloud computing plug-in;

[0129] Upload the calculation and solution working directory to the cloud, execute the solution operation instructions through the cloud, and obtain the cloud solution results;

[0130] Send the cloud solution results to the local terminal for download;

[0131] The cloud computing service provides cloud computing API interfaces and cloud computing supporting services to realize the development of CAE-side cloud computing plug-ins, and realizes cloud computing by calling the cloud computing API.

[0132] Optionally, it also includes:

[0133] Receive user requests through the API component and verify user permissions through the security component;

[0134] When the verification is passed, the user request is pushed to the access control component, which identifies the cloud upload operation and sends a cloud upload request to the data management component;

[0135] Uploaded files are stored through the data storage layer of the data management component.

[0136] Specifically, the CAE cloud computing plug-in design method of this embodiment is as follows: Figure 2 As shown:

[0137] S1: The CAE cloud computing plug-in is loaded and starts running;

[0138] S2: The CAE cloud computing plug-in will monitor whether the operation of outputting the solution file to the working directory is completed. If it is completed, it will jump to step S3. If it is not completed, it will block and wait;

[0139] S3: The CAE cloud computing plug-in determines whether the user enables cloud computing. If yes, it jumps to step S4. If not, it performs CAE local solution and jumps to step S7.

[0140] S4: The CAE cloud computing plug-in uploads the solution working directory to the cloud;

[0141] S5: CAE cloud computing plug-in enables cloud computing to solve examples;

[0142] S6: After the example is solved, the CAE cloud computing plug-in downloads the result file to the specified path;

[0143] S7: Convert the result file into a specific format file such as table data or VTK data;

[0144] S8: The CAE post-processing module displays the specific format file in two-dimensional or three-dimensional images to complete the entire solution process.

[0145] Furthermore, if Figure 3 and Figure 4 As shown, Figure 3 This is the CAE local solution mode diagram. Figure 4 This is a diagram of the CAE cloud solution mode; CAE has achieved a leap from the local solution mode to the cloud solution mode, breaking through the limitations of local hardware performance, and using high-performance server clusters to improve the solver's single-core CPU performance and the upper limit of the number of parallel solution CPU cores, greatly improving CAE solution efficiency. The CAE cloud solution mode execution process is as follows:

[0146] S10: CAE pre-processing module completes geometric model drawing, meshing, working condition parameter setting and solver setting;

[0147] S20: CAE solution driver and process control module call solver;

[0148] S30: After the solver outputs the solution model information as a solution file and stores it in the local solution unit working directory, it sends a local solution unit enable signal. After the cloud computing plug-in cloud computing enable signal monitoring unit of the CAE end captures the signal, it determines whether cloud computing is enabled. If so, the local solution unit is blocked from solving and the cloud computing unit is enabled.

[0149] S40: The cloud computing unit of the cloud computing plug-in on the CAE end uploads the solver working directory and solution information to the cloud;

[0150] S50: The cloud computing unit of the cloud computing plug-in at the CAE end releases the computing task and starts the cloud solver. The cloud solver automatically obtains the solution file in the working directory as input and starts solving. Meanwhile, during the execution of the cloud solver, the solver solution process information and solution progress can be fed back to the local UI interface in real time through the API interface. After the cloud solver solves, the result file is obtained, and a solution completion signal is sent to the cloud computing unit of the cloud computing plug-in at the CAE end.

[0151] S60: After receiving the solution completion signal from the cloud solver, the cloud computing unit of the CAE-side cloud computing plug-in automatically downloads the result file to the specified path, and the result unified output unit outputs the result file;

[0152] S70: The solver outputs the result file as a specific format file such as table data or VTK data;

[0153] S80: The CAE post-processing module renders and displays specific format files such as table data or VTK data in the CAE two-dimensional or three-dimensional graphical interface.

[0154] It can be understood that the detailed functional implementation of each of the above-mentioned units / modules can be found in the introduction of the aforementioned method embodiment, and will not be repeated here.

[0155] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the device are similar to those described in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method, which will not be repeated here.

[0156] Reference Figure 5 Based on the method in the above embodiment, the embodiment of the present application provides an electronic device, which may include: a processor (processor) 510, a communication interface (CommunicationsInterface) 520, a memory (memory) 530 and a communication bus 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other through the communication bus 540. The processor 510 can call the logic instructions in the memory 530 to execute the method in the above embodiment.

[0157] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0158] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0159] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0160] It is understandable that the processor in the embodiment of the present application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0161] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0162] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0163] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0164] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A CAE performance optimization system, characterized in that: It includes CAE local end and cloud server cluster; the local end deploys cloud computing plug-in, and the server cluster deploys cloud computing service: The cloud computing plug-in is used to automatically shield CAE local solution operation instructions when the user uses the local solution unit to solve the problem on the local side; upload the calculation solution working directory to the cloud, so that the cloud executes the solution operation instructions to obtain the cloud solution result, and receive the solution result sent by the cloud to the local side for download; The cloud computing service is used to realize the development of CAE-side cloud computing plug-ins by providing cloud computing API interfaces and cloud computing supporting services to the outside world, and to realize cloud computing and interaction between the local side and the cloud by calling the cloud computing API interfaces.

2. The CAE solution performance optimization system according to claim 1, characterized in that: The cloud computing plug-in integrates cloud computing functions into CAE and is compatible with the local solution unit of CAE; The cloud computing plug-in includes an enabling signal monitoring unit, a cloud computing unit, and an output unit; An enabling signal monitoring unit, used to determine whether the user enables cloud computing after the local solving unit completes solving and outputs a solution file, and to disable the local solving unit and enable the cloud computing unit when the determination result is yes; The cloud computing unit interacts with the cloud through an API interface to upload the solution working directory to the cloud, perform solution in the cloud, and download the solution results; The output unit is used to uniformly output the solution results of the local solution unit and the calculation results of the cloud computing unit.

3. The CAE solution performance optimization system according to claim 1, characterized in that: The local end includes a pre-processing module, a solution drive and process control module, a local solution module and a post-processing module; The pre-processing module is used to draw the geometric model, divide the mesh, set the working parameters and solver, and determine the solution model information; The solution drive and process control module is used to call the solver to perform the solution task; The local solution module is used to output the solution model information as a solution file, store the solution file in a local solution working directory, and send an enable signal to the cloud computing plug-in.

4. The CAE solution performance optimization system according to claim 3, characterized in that: The enable signal monitoring unit is further used to, when the judgment result is no, use the local solution unit to perform local solution, output the result file of the local solution, and convert the result file into a specific format file of tabular data or VTK data; The local end also includes a post-processing module; The post-processing module is used to display the specific format file output from the cloud in two-dimensional or three-dimensional images.

5. The CAE solution performance optimization system according to claim 1, characterized in that: The cloud computing service includes an API component, an access control component, a security component, a data management component, and a node management component; The API component is used to provide an interactive interface between external applications and cloud computing services, call cloud computing resources and submit computing tasks according to user input, and obtain computing results; The access control component is used to manage and authorize users' access rights to cloud computing services to implement user registration, login, permission allocation and identity authentication; The security component is used to provide security for CAE cloud computing services, prevent illegal access, data leakage and malicious attacks, and provide data encryption, identity authentication and firewall; The data management component is used to manage and store data in the cloud computing service; The node management component is used to manage and schedule computing nodes in cloud computing services to achieve dynamic allocation and load balancing of computing resources.

6. The CAE solution performance optimization system according to claim 5, characterized in that: The API components include: at least one of a user registration interface, a user login interface, a file upload interface, a file download interface, a file list acquisition interface, a computing task submission interface, a computing task status query interface, and a computing task cancellation interface.

7. A CAE solution performance optimization method, characterized in that: Applied to CAE software system, the software system includes a local end and a server cluster in the cloud; the local end deploys a cloud computing plug-in, and the server cluster deploys a cloud computing service, the method includes: When the user uses the local solution unit to solve on the local side, the CAE local solution operation instructions are automatically shielded by the cloud computing plug-in; Upload the calculation and solution working directory to the cloud, execute the solution operation instructions through the cloud, and obtain the cloud solution results; Send the cloud solution results to the local terminal for download; The cloud computing service provides cloud computing API interfaces and cloud computing supporting services to realize the development of CAE-side cloud computing plug-ins, and realizes cloud computing by calling the cloud computing API.

8. The CAE solution performance optimization method according to claim 7, characterized in that: Also includes: Receive user requests through the API component and verify user permissions through the security component; When the verification is passed, the user request is pushed to the access control component, which identifies the upload cloud operation and sends the upload cloud request to the data management component; Uploaded files are stored through the data storage layer of the data management component.

9. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory, when the program stored in the memory is executed, the processor is used to execute the method according to claim 7 or 8.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program runs on a processor, the processor is caused to execute the method according to any one of claims 7 or 8.

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