A CAE solution performance optimization system and method

Abstract

This application belongs to the field of cloud computing technology, and specifically discloses a CAE solution performance optimization system and method. The system includes a CAE local terminal and a cloud server cluster; the local terminal deploys a cloud computing plug-in, and the server cluster deploys a cloud computing service: the cloud computing plug-in is used to automatically shield the CAE local solution operation instructions when the user uses the local solution unit to solve the problem on the local terminal; the solution working directory is uploaded to the cloud, so that the cloud executes the solution operation instructions, obtains the cloud solution result, and receives the solution result sent by the cloud to the local terminal for download; the cloud computing service is used to realize the development of the CAE cloud computing plug-in by providing a cloud computing API interface and cloud computing supporting services to the outside world, and realizes cloud computing and interaction between the local terminal and the cloud by calling the cloud computing API interface. Through this application, the solution efficiency of CAE can be improved.

Description

Technical Field

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

[0002] In recent years, driven by concerns about information security and independent control, domestic demand for domestically produced industrial software has been growing. As a key branch of industrial software, CAE is also accelerating its domestic substitution process. As the domestic production rate increases, CAE needs to compete with international brands in 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 needs of 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 their self-developed solvers into standard CAE modules to achieve rapid productization.

[0004] However, the solving performance of CAE solvers is generally limited by factors such as the solving algorithm and model, the solver's 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, CAE's solving efficiency 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 existing technology, 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 solution performance optimization system, comprising a CAE local terminal and a cloud server cluster; 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 block 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 results, and receive the solution results 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 end and the cloud by calling the cloud computing API interfaces.

[0010] The CAE-side cloud computing plug-in of this 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 cloud solution result download; 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 cloud solution result download on the CAE side. This application achieves 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, this 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 CAE solution efficiency.

[0011] Optionally, the cloud computing plug-in integrates cloud computing functionality into CAE and achieves compatibility with CAE's local solution unit;

[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, configured to determine whether the user has enabled cloud computing after the local solving unit has completed solving and output a solution file, and to disable the local solving unit and enable the cloud computing unit if 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 processing on 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 configured to, when the judgment result is negative, perform local solution using the local solution unit, output a 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 or three dimensions.

[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. The software system includes a local terminal and a server cluster in the cloud. A cloud computing plug-in is deployed on the local terminal, and a cloud computing service is deployed on the server cluster. The method includes:

[0031] When the user uses the local solution unit to solve the problem on the local side, the cloud computing plug-in is used to automatically block the CAE local solution operation instructions;

[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 the outside world 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] Once 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;

[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, which, when executed on a processor, enables the processor to execute 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 existing technologies:

[0044] (1) The CAE-side cloud computing plug-in of this 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; the cloud computing service is deployed on the server cluster, which is used to provide cloud computing API interfaces and cloud computing supporting services to the outside world. CAE users can quickly realize the development of CAE-side cloud computing plug-ins 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. This application achieves 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, this 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 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, simplifying user operations and reducing 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 needs of different users and changes in computing tasks. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

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

[0051] Figure 4 This is a diagram of the CAE cloud solution model provided by an embodiment of the present application;

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

[0053] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0054] The term "and / or" as used herein describes an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. The symbol " / " as used herein indicates that the related objects are in an "or" relationship, for example, A / B means either A or B.

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

[0056] In the embodiments of this 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 this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

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

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

[0059] This application provides a CAE solution performance optimization system, including a CAE local terminal and a cloud server cluster; the local terminal 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 block 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 results, and receive the solution results 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 end 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 side:

[0064] A cloud computing plug-in will be deployed locally to serve as a bridge between the user and the cloud server cluster. When the user uses the local solver to perform simulations or calculations 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 capable of processing multiple solution tasks in parallel. These servers are equipped with hardware and software optimized for CAE tasks, enabling rapid execution of computational tasks and the return of results. The cloud computing service will provide an API interface for local cloud computing plug-ins to access, upload, execute, and return results of computational tasks.

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

[0069] First, the task is identified and uploaded. The user defines the computational task locally using the solver. Once the working directory is uploaded, the cloud server cluster begins solving the problem according to the received computational task instructions. This process involves scheduling computing resources, executing the solution algorithm, and performing any necessary post-processing. Upon completion, the cloud generates the solution results and transmits them to the local client. The cloud computing plug-in receives the results and downloads 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 APIs that allow the CAE local plug-in to interact with the cloud server. These APIs will cover the following functions: receiving solution tasks uploaded by the local client and returning the task processing status; allowing the local client to query the execution status of solution tasks in the cloud; and providing a secure and efficient way for users to download cloud-based calculation results.

[0071] The CAE solution performance optimization system in this application utilizes 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 capability, which can provide higher computing performance than the average local computer. By utilizing multiple CPU cores and nodes in the cloud, multiple computing tasks can be processed in parallel or multiple cores can be allocated to 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, ensuring 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 functionality into CAE and achieves compatibility with CAE's local solution unit;

[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, configured to determine whether the user has enabled cloud computing after the local solving unit has completed solving and output a solution file, and to disable the local solving unit and enable the cloud computing unit if 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 processing on 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 needed.

[0079] The enable signal monitoring unit is responsible for monitoring the status of the local solver and whether the user has enabled the cloud computing function. When the local solver 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 to achieve 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 from the cloud platform and performing calculations based on them. It automatically retrieves the solution files in the working directory and uses them as calculation input based on the cloud environment. Through an API interface, it interacts with the local user interface in real time, providing users with important information about the calculation process, including solution progress and current status. This allows users to understand the real-time status of the cloud solver and effectively manage their computing 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 locally 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 begins to monitor 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 solver is disabled and the cloud computing unit is activated. If not, the local solver continues to output the results.

[0090] If the cloud computing unit is activated, the solution file in the working directory is 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 on 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 formats and displays them uniformly through the output unit.

[0093] The embodiments of this application integrate 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 configured to, when the judgment result is negative, perform local solution using the local solution unit, output a 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 or three dimensions.

[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 to 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 driver and process control module is responsible for controlling the solution process and coordinating the execution of the solver.

[0103] Based on 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 to handle abnormal situations during 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 solver is to convert the solution model information generated by the pre-processing module into a solution file and execute the calculation task. Based on the set model and operating parameters, a solution file containing all necessary information is generated for the solver to use. The generated solution file is saved in the local solver working directory for easy review and management. After the solution file is output, the module sends an enable signal to the cloud computing plug-in to determine whether cloud computing resources will be used later.

[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] In the pre-processing module, the user creates a geometric model and sets analysis parameters, completing model construction and configuration. After completing pre-processing, the solver driver and process control module invokes the local solver to execute the solution. The local solver generates the solution file and stores it in the local working directory. At this point, an enable signal is simultaneously sent to the cloud computing plug-in. The local solver performs the corresponding calculations based on the input file and outputs the results. The post-processing module reads and analyzes the solution results, presenting them to the user for further use and analysis.

[0109] This embodiment of the application rationally divides local functional modules to provide necessary support for each stage of the solution process, thereby improving computing efficiency and user experience. The system can not only meet users' needs for local solutions, but also facilitate the use of cloud computing resources when needed, demonstrating 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 Figure 1, cloud computing services include API components, access control components, security components, data management components, and node management components. For example, when a client calls the upload cloud API, the API component receives the user request, the security component verifies user permissions, and if approved, pushes the request to the access control component. The access control component recognizes the upload cloud operation and sends a request to the data management component. Ultimately, 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, submit computing tasks, and obtain computing results through programming.

[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, realizing 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, this embodiment of the application designs a set of cloud computing service API interfaces. The cloud computing service API interface design includes an interface name, interface description, interface request parameters, and interface response parameters. The cloud computing service provides standard API calls to the outside world, enabling 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, computing task submission, computing task status query, and computing task cancellation.

[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. The software system includes a local terminal and a server cluster in the cloud. A cloud computing plug-in is deployed on the local terminal, and a cloud computing service is deployed on the server cluster. The method includes:

[0128] When the user uses the local solution unit to solve the problem on the local side, the cloud computing plug-in is used to automatically block the CAE local solution operation instructions;

[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 the outside world 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] Once 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;

[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 monitors whether the output of the solution file to the working directory is completed. If it is completed, it jumps to step S3. If not, it blocks and waits.

[0139] S3: The CAE cloud computing plug-in determines whether the user has enabled cloud computing. If so, the process jumps to step S4. If not, the CAE local solution is performed and the process 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 and solves case studies;

[0142] S6: After the calculation is completed, 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 tabular data or VTK data;

[0144] S8: The CAE post-processing module displays the files in a specific format in two or three dimensions 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-based solution model. CAE has achieved a leap from local solution model to cloud-based solution model, breaking through the limitations of local hardware performance. By utilizing high-performance server clusters, the solver's single-core CPU performance and the upper limit of the number of CPU cores for parallel solution are improved, greatly improving CAE solution efficiency. The execution process of the CAE cloud-based solution model is as follows:

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

[0147] S20: CAE solver 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 solver unit working directory, it sends a local solver unit enable signal. After the cloud computing enable signal monitoring unit of the CAE cloud computing plug-in captures the signal, it determines whether cloud computing is enabled. If so, it blocks the local solver unit from solving and enables the cloud computing unit.

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

[0150] S50: The cloud computing unit of the CAE-side cloud computing plug-in publishes a computing task and starts the cloud solver. The cloud solver automatically obtains the solution file in the working directory as input and starts solving. During the execution of the cloud solver, the solver's solution process information and solution progress can be fed back to the local UI interface in real time through the API interface. When the cloud solver completes the solution, a result file is obtained and a solution completion signal is sent to the cloud computing unit of the CAE-side cloud computing plug-in.

[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 tabular data, VTK data, and other files in specific formats on the CAE 2D or 3D graphical interface.

[0154] It is understandable that the detailed functional implementation of each of the above 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 and will not be repeated here.

[0156] Reference Figure 5 Based on the method in the above embodiment, an embodiment of the present application provides an electronic device, which may include: a processor (processor) 510, a communication interface (Communications Interface) 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 via 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 a software functional unit 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. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute 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 understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may be 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 may 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, which 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 the 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 can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can 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 drive (SSD)).

[0163] It will be understood that the various numerical numbers involved in the embodiments of the present application are merely distinctions for the convenience of description and are not intended to limit the scope of the embodiments of the present application.

[0164] It is easy for those skilled in the art to understand that the above 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 should be included in the scope of protection of the present application.

Claims

1. A CAE solution 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 services: The cloud computing plug-in is used to automatically block 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 results, and receive the solution results sent by the cloud to the local side for download; The cloud computing plug-in includes an enable signal monitoring unit, which is used to determine whether the user has enabled cloud computing after the local solution unit completes the solution and outputs the solution file. When the judgment result is yes, the local solution unit is shielded and the cloud computing unit is enabled; the cloud computing service is used to realize the development of 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 end 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 achieves compatibility with CAE's local solution units; The cloud computing plug-in further includes a cloud computing unit and an output unit; The cloud computing unit interacts with the cloud through an API interface to upload the solution working directory to the cloud, perform solution processing on 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 configured to, when the judgment result is negative, use the local solution unit to perform local solution, output a 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 or three dimensions.

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 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 a CAE software system, the software system includes a local terminal and a server cluster in the cloud; a cloud computing plug-in is deployed on the local terminal, and a cloud computing service is deployed on the server cluster. The method includes: When the user uses the local solution unit to solve the problem on the local side, the cloud computing plug-in is used to automatically block the CAE local solution operation instructions; After the local solution unit completes the solution and outputs the solution file, it is determined whether the user has enabled cloud computing. If the determination result is yes, the local solution unit is disabled and the cloud computing unit is enabled. 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 the outside world to realize the development of cloud computing plug-ins, and realizes cloud computing by calling the cloud computing API interfaces.

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; Once 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 configured to execute the program stored in the memory, and when the program stored in the memory is executed, the processor is configured 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 is run on a processor, the processor is caused to perform the method according to any one of claims 7 or 8.

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