A cloud-based real-time simulation calculation method, system, device, and storage medium

Abstract

The present application provides a cloud real-time simulation calculation method, system, device, and storage medium. The method includes: the front end receives a design scheme update instruction input by a user, generates change data based on the design scheme update instruction, and sends the change data to the cloud simulation service; the cloud simulation service performs incremental data change on the simulation scenario data in the memory based on the change data to obtain the changed simulation scenario data; performs simulation calculation on the changed simulation scenario data to obtain a simulation result, and saves the changed simulation scenario data in the memory; the cloud simulation service sends the simulation result to the front end. According to the solution of the present application, real-time high-precision simulation can be achieved, thereby improving the simulation experience of users.

Description

Technical Field

[0001] The present application relates to the field of simulation technology, and in particular, to a cloud real-time simulation calculation method, system, electronic device, and storage medium. Background Art

[0002] In the existing simulation technology, after the front-end receives the design scheme input by the user, it calculates the simulation scenario data and performs simulation calculations on the simulation scenario data to obtain simulation results. This is a full-scale simulation method, that is, every time the user updates the design scheme, it is necessary to recalculate the simulation scenario data, resulting in too slow simulation speed. The user cannot intuitively feel the simulation effect and numerical changes during the design process, and needs to repeatedly adjust and confirm the simulation effect, which seriously affects the work efficiency of designers. Moreover, continuous simulation also increases the data storage and maintenance costs. In addition, due to the limited hardware configuration of personal computers and the complex calculations involved in simulation calculations, the accuracy and quality of real-time simulation based on the front-end are low, and the burden on the front-end device is heavy. Summary of the Invention

[0003] The present application provides a cloud real-time simulation calculation method, device, equipment, and storage medium to solve or alleviate one or more technical problems in the prior art.

[0004] In a first aspect, the present application provides a cloud real-time simulation calculation method, including:

[0005] The front-end receives a design scheme update instruction input by the user, generates change data based on the design scheme update instruction, and sends the change data to the cloud simulation service;

[0006] The cloud simulation service performs incremental data changes on the simulation scenario data in the memory based on the change data to obtain the changed simulation scenario data; performs simulation calculations on the changed simulation scenario data to obtain simulation results, and saves the changed simulation scenario data in the memory;

[0007] The cloud simulation service sends the simulation results to the front-end.

[0008] In a second aspect, the present application provides a cloud real-time simulation calculation system, including:

[0009] A front-end for receiving a design scheme update instruction input by the user, generating change data based on the design scheme update instruction, and sending the change data to the cloud simulation service;

[0010] A cloud simulation service is used to perform incremental data changes on the simulation scenario data in memory based on the changed data to obtain the changed simulation scenario data; perform simulation calculations on the changed simulation scenario data to obtain simulation results, and save the changed simulation scenario data in memory; and send the simulation results to the front end.

[0011] In a third aspect, an electronic device is provided, including:

[0012] At least one processor; and

[0013] A memory communicatively connected to the at least one processor; wherein,

[0014] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute any method in the embodiments of the present application.

[0015] In a fourth aspect, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute any method in the embodiments of the present application.

[0016] In a fifth aspect, a computer program product is provided, including a computer program, and the computer program implements any method in the embodiments of the present application when executed by a processor.

[0017] Combining the high precision of offline simulation and the real-time efficiency of the front end, the embodiments of the present application propose a cloud real-time simulation technology. The front end generates update data based on the design scheme update instructions input by the user and sends it to the cloud simulation service in real time; the cloud simulation service performs incremental data changes on the simulation scenario data loaded in memory based on the changed data to obtain the changed simulation scenario data, and performs simulation calculations on the changed simulation scenario data, avoiding the inefficiency of traditional full-scale simulation, improving the simulation speed, achieving the effect of previewing while designing, and reducing data storage and maintenance costs. In addition, since the simulation ability is migrated to the cloud simulation service, the front end only needs to process simple calculations, and complex calculations are completed by the cloud simulation service, thereby improving the accuracy and quality of the simulation and reducing the burden on the front-end device. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In the drawings, unless otherwise specified, the same reference numerals throughout the several views denote the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments provided according to the present application and should not be regarded as limiting the scope of the present application.

[0019] Figure 1It is a schematic flowchart of a cloud-based real-time simulation calculation method according to an embodiment of the present application;

[0020] Figure 2 It is a schematic flowchart of the simulation initialization process in a cloud-based real-time simulation calculation method according to an embodiment of the present application;

[0021] Figure 3 It is a flowchart for implementing Embodiment 1 of the present disclosure;

[0022] Figure 4 It is a schematic structural diagram of a cloud-based real-time simulation calculation system 400 according to an embodiment of the present disclosure;

[0023] Figure 5 It is a schematic structural diagram of a cloud-based real-time simulation calculation system 500 according to an embodiment of the present disclosure;

[0024] Figure 6 It is a structural block diagram of an electronic device according to an embodiment of the present application. Detailed implementation manners

[0025] Hereinafter, the present application will be further described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements having the same or similar functions. Although various aspects of the embodiments are shown in the drawings, the drawings do not have to be drawn to scale unless otherwise specified.

[0026] In addition, for better illustration of the present application, numerous specific details are given in the following detailed implementation manners. Those skilled in the art should understand that the present application can also be implemented without some of these specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art are not described in detail so as to highlight the gist of the present application.

[0027] At the present stage, the general simulation method is the full-scale simulation method. The simulation speed of this method is too slow, the data storage and maintenance costs are too high, the accuracy and quality of the real-time simulation based on the front end are low, and the burden on the front-end device is heavy. Taking lighting simulation as an example, there are mainly the following two types of lighting simulation at the present stage:

[0028] 1. Ray tracing offline simulation with indirect light. In this method, after the user builds a scene, the scene data of the simulation scheme is calculated asynchronously in the background and submitted to the simulation engine for offline rendering.

[0029] 2. Real-time rendering with only direct light. Real-time rendering updates the direct light simulation results caused by changes in lamps or scenes in real time during the operation according to the data of the Illuminating Engineering Society (IES) file.

[0030] The above simulation method has at least the following disadvantages:

[0031] First, the offline simulation speed is slow: During the design process, users cannot intuitively feel the simulation effect and numerical changes, and need to repeatedly adjust and render for confirmation, which seriously affects the work efficiency of designers.

[0032] Second, the cost of persisting simulation results is high: In order to confirm the effect, users need to continuously simulate, increasing the data storage and maintenance costs.

[0033] Third, hardware configuration limitations: Due to the limited hardware configuration of users' personal computers, when considering real-time simulation based on the front end, browser performance issues need to be emphasized. Therefore, only some simple calculations can be performed when calculating real-time lighting effects, sacrificing some effects and accuracy, and only pseudo-color maps of direct light can be output, unable to handle complex calculations.

[0034] In view of the above problems, the embodiments of the present application propose a cloud real-time simulation calculation method and system, which combines the high precision of offline simulation and the high efficiency of front-end real-time to achieve real-time high-precision simulation, thereby improving the simulation experience of users.

[0035] For the convenience of subsequent description, each part of the cloud real-time simulation calculation system in the embodiments of the present application will be explained below.

[0036] Front end: The front-end browser, such as the "lighting design" tool in the front-end browser.

[0037] Cloud simulation service: Deployed in the cloud, including Streaming (streaming service) and a simulation engine; among them, Streaming is a microservice architecture that establishes long connections with the front end and the simulation engine respectively through the WebSocket protocol; the simulation engine is used for simulation calculations.

[0038] Simulation data conversion service: Deployed in the cloud, including the simulation middle and back-end services, which is a microservice architecture.

[0039] Figure 1 The cloud real-time simulation calculation method of the embodiments of the present application includes:

[0040] S110. The front end receives a design scheme update instruction input by the user, generates change data based on the design scheme update instruction, and sends the change data to the cloud simulation service;

[0041] S120. The cloud simulation service makes incremental data changes to the simulation scenario data in the memory based on the change data to obtain the changed simulation scenario data; performs simulation calculations on the changed simulation scenario data to obtain simulation results, and saves the changed simulation scenario data in the memory;

[0042] S130. The cloud simulation service sends the simulation result to the front end.

[0043] After receiving the simulation result, the front end can display the simulation result.

[0044] In the cloud real-time simulation calculation method provided by the embodiments of the present application, the cloud simulation service always saves the latest simulation scenario data throughout the simulation period. After receiving the change data sent by the front end, the cloud simulation service uses the change data to perform incremental data changes on the currently saved simulation scenario data, thereby updating the saved simulation scenario data; uses the changed simulation scenario data for simulation calculation, and saves the latest simulation scenario data.

[0045] The embodiments of the present application have at least the following advantages:

[0046] (1) By using the real-time incremental calculation function of the cloud simulation service, the inefficiency problem of traditional full-scale simulation is avoided, the simulation speed is improved, enabling users to generate images within seconds, achieving the effect of previewing while designing, and significantly improving work efficiency.

[0047] (2) Since there is no need to repeatedly persist the simulation results, the storage requirements for offline simulation data are greatly reduced, thereby reducing the storage cost and alleviating the resource pressure on the offline simulation server, and improving the resource utilization efficiency of the overall system.

[0048] (3) Since the simulation ability is migrated to the cloud, the front end only needs to process simple calculations, and complex calculations are completed by the cloud simulation service, ensuring high-precision and high-quality simulation effects, while reducing the burden on the front-end device.

[0049] Figure 1 The process shown involves the scenario of updating the design scheme during the simulation process. Before this, it may also include a simulation initialization process. For example, as Figure 2 shown, before the above step S110, it may also include:

[0050] S210. The front end receives the user's simulation request;

[0051] S220. The cloud simulation service constructs initial full-scale simulation scenario data based on the simulation request, performs simulation calculation on the initial full-scale simulation scenario data to obtain an initial simulation result, and saves the initial full-scale simulation scenario data in memory;

[0052] S230. The cloud simulation service sends the initial simulation result to the front end.

[0053] After the initialization process, the cloud simulation service saves the initial full-scale simulation scenario data in memory; during subsequent solution update processes, each time the cloud simulation service receives change data sent from the front end, it changes the currently saved simulation scenario data (when initially receiving the change data, the currently saved simulation scenario data is the initial full-scale simulation scenario data). When the front end receives a user's simulation stop request, or when no user change requests are received within a preset threshold range, the cloud simulation service deletes the changed simulation scenario data saved in memory.

[0054] In some embodiments, to further improve the simulation speed, without sacrificing simulation accuracy, complex rendering effect-based material properties can be simplified, and the rendering material can be converted into a simulation material.

[0055] In one example, a simulation data conversion service can be used to convert the simulation material. For example, in the above process, generating change data based on the design solution update instruction includes: the front end calls the simulation data conversion service, and the simulation data conversion service converts the rendering material into a simulation material, and constructs change data on this basis.

[0056] After that, the front end sends this change data to the cloud simulation service.

[0057] Simulation materials do not need to focus on the effect performance in the real world, but only focus on the energy transfer changes in the interaction between materials and light. Therefore, more refined material properties such as texture maps in the rendering material (such as wood grain, marble, etc.) can be ignored, and complex effect material nodes can be ignored, and converted into the basic properties of the simulation material. By simplifying this part of complex material data, it can be infinitely magnified without distortion during rendering, avoiding the resolution limitations of image mapping, and at the same time greatly improving the simulation calculation speed.

[0058] In some embodiments, the simulation calculation process includes data processing and calculation. In one example, the above-mentioned simulation calculation of the changed simulation scenario data includes:

[0059] The cloud simulation service loads the changed simulation scenario data and processes the changed simulation scenario data to obtain simulation intermediate data;

[0060] The cloud simulation service analyzes and calculates the simulation intermediate data based on the simulation parameters set by the user, and displays the results of the analysis and calculation in a Low Dynamic Rangle (LDR) image or vector diagram.

[0061] Among them, the simulation parameters set by the user can include a color bar or a Unified Glare Rating (UGR), etc.

[0062] The following is a detailed introduction to this application with specific embodiments in conjunction with the accompanying drawings.

[0063] Figure 3 is the implementation flowchart of Embodiment 1 of the present disclosure. In the Figure 3 illustrated example, the cloud simulation service includes Streaming streaming service and simulation engine, and the simulation data conversion service includes simulation background services as an example for introduction.

[0064] As Figure 3 shown, this implementation process includes the following three stages:

[0065] The first stage: Authentication, including the following steps:

[0066] S301. The user opens the "Real-time Preview" window in the "Lighting Design" plugin. At this time, the front end will request a token from Streaming.

[0067] S302. Streaming authenticates the front-end request. After successful authentication, it distributes the token to the front end.

[0068] The second stage: Initializing the scene, including the following steps:

[0069] S303. After the front end obtains the token, it establishes a long connection with Streaming through the WebSocket protocol and simultaneously requests the simulation data conversion service to generate simulation scene data (such as kescene scene data).

[0070] S304. The simulation data conversion service constructs simulation scene data based on the solution at the moment of opening the "Real-time Preview". In order to reduce the rendering duration and without affecting the simulation accuracy, the rendering material can be converted into a simulation material at this time. After the conversion is completed, the simulation scene data is uploaded to the cloud object storage (Cloud Object Storage, COS) service, and at the same time, the COS key (KEY) and the task identifier (task ID) are returned to the front end.

[0071] S305. The front end submits information such as the token, task ID, and COS KEY to Streaming.

[0072] S306. Streaming downloads the simulation scene data from the COS service based on the received task ID, COS KEY, etc., and submits the simulation scene data to the simulation engine.

[0073] S307. The simulation engine loads the simulation scene data.

[0074] S308. The simulation engine processes the simulation scenario data to obtain intermediate simulation data such as high dynamic range (HDR) images, JSON files, and channel maps. The simulation scenario data at this time will be continuously loaded in memory until it is released after the connection is disconnected.

[0075] S309. After the simulation engine finishes the simulation, it will notify the post-simulation processing to perform data processing and calculation. At this time, the post-simulation processing starts working. First, it will load the intermediate simulation data (such as HDR images, JSON files, channel maps, etc.) and the simulation parameters set by the user (such as color bars, UGR, etc.), and then parse and calculate the intermediate simulation data based on the simulation parameters, and display the results of the parsing and calculation in an LDR image or a vector image.

[0076] S310. The simulation engine sends simulation results such as LDR images and vector images to Streaming, and Streaming returns the simulation results to the front end in the form of a binary stream.

[0077] The third stage: Update the scenario, including the following steps:

[0078] S311. The user updates the scheme design in the lighting tool (such as changing the position of the lighting model, updating materials or lighting data, etc.), or sets simulation parameters (such as color bars, UGR, etc.), triggering an incremental update of the simulation.

[0079] At this time, the front end will record the changed data, and at the same time, it will call the simulation data conversion service for the newly added models or data with material changes in the scheme. The simulation data conversion service will convert the rendering materials into simulation materials, construct the changed data on the basis of the conversion, and return the changed data (such as pbrjson data) to the front end.

[0080] S312. The front end will submit the changed data to Streaming after the user's operation is completed.

[0081] S313. Streaming submits the changed data to the simulation engine and requests a simulation.

[0082] S314. The simulation engine initiates an incremental data change based on the simulation scenario data in memory, obtains the changed simulation scenario data, and processes the changed simulation scenario data to obtain intermediate simulation data such as HDR files, JSON files, and channel maps.

[0083] After the simulation engine finishes the simulation, it will notify the post-simulation processing to process and calculate the data. At this time, the post-simulation processing starts to work. First, it will load the intermediate simulation data (such as HDR images, JSON files, channel maps, etc.) and the simulation parameters set by the user (such as color bars, UGR, etc.), and then parse and calculate the intermediate simulation data based on the simulation parameters, and display the results of the parsing and calculation in an LDR image or a vector image.

[0084] S315. The simulation engine sends simulation results such as LDR images and vector images to Streaming, and Streaming returns the simulation results to the front end in the form of a binary stream.

[0085] Until the front end receives the user's request to stop the simulation, or when no change request from the user is received within the preset threshold range, the simulation engine deletes the simulation scenario data saved in the memory and releases the memory.

[0086] An embodiment of the present application also proposes a cloud real-time simulation calculation system. Figure 4 FIG. 400 is a schematic structural diagram of a cloud real-time simulation calculation system according to an embodiment of the present disclosure, including a front end 410 and a cloud simulation service 420; wherein,

[0087] The front end 410 is configured to receive a design scheme update instruction input by a user, generate change data based on the design scheme update instruction, and send the change data to the cloud simulation service.

[0088] The cloud simulation service 420 is configured to perform incremental data change on the simulation scenario data in the memory based on the change data to obtain the changed simulation scenario data; perform simulation calculation on the changed simulation scenario data to obtain a simulation result, and save the changed simulation scenario data in the memory; send the simulation result to the front end.

[0089] In some embodiments, the front end 410 is further configured to receive a simulation request from the user.

[0090] The cloud simulation service 420 is further configured to construct initial full-scale simulation scenario data based on the simulation request, perform simulation calculation on the initial full-scale simulation scenario data to obtain an initial simulation result, and save the initial full-scale simulation scenario data in the memory; send the initial simulation result to the front end.

[0091] An embodiment of the present application also proposes a cloud real-time simulation calculation system. Figure 5 FIG. 500 is a schematic structural diagram of a cloud real-time simulation calculation system according to an embodiment of the present disclosure, including a front end 410, a cloud simulation service 420, and a simulation data conversion service 530; wherein,

[0092] The simulation data conversion service 530 is used to convert the rendering material into a simulation material based on a front-end call, and construct the change data on the basis of the conversion.

[0093] In some embodiments, the cloud simulation service 420 is used to load the changed simulation scene data, process the changed simulation scene data to obtain simulation intermediate data; based on the simulation parameters set by the user, parse and calculate the simulation intermediate data, and display the results of the parsing and calculation in a low-dynamic range image or a vector map.

[0094] In some embodiments, the simulation intermediate data includes at least one of a high-dynamic range image, a JSON file, and a channel map.

[0095] In some embodiments, the cloud simulation service 420 is further used to delete the changed simulation scene data stored in the memory when a stop simulation request from the user is received at the front end, or when no change request from the user is received within a preset threshold range.

[0096] For the specific functions and examples of the modules and sub-modules of the device in the embodiments of the present application, reference may be made to the relevant descriptions of the corresponding steps in the above method embodiments, which will not be elaborated here.

[0097] In the technical solution of the present application, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0098] Figure 6 It is a structural block diagram of an electronic device according to an embodiment of the present application. As Figure 6 shown, the electronic device includes: a memory 610 and a processor 620. The memory 610 stores a computer program that can run on the processor 620. The number of the memory 610 and the processor 620 can be one or more. The memory 610 can store one or more computer programs. When the one or more computer programs are executed by the electronic device, the electronic device executes the method provided in the above method embodiments. The electronic device may further include: a communication interface 630, which is used to communicate with external devices and perform data interaction and transmission.

[0099] If the memory 610, the processor 620, and the communication interface 630 are implemented independently, the memory 610, the processor 620, and the communication interface 630 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 only a thick line is used in

[0100] to represent it, but it does not mean that there is only one bus or one type of bus. Optionally, in specific implementation, if the memory 610, the processor 620, and the communication interface 630 are integrated on a chip, the memory 610, the processor 620, and the communication interface 630 can communicate with each other through an internal interface.

[0101] It should be understood that the above-mentioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. It is worth noting that the processor can be a processor that supports the Advanced RISC Machines (ARM) architecture.

[0102] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may further include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM).

[0103] 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 instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wireless (such as infrared, Bluetooth, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a Digital Versatile Disc (DVD)), or a semiconductor medium (such as a Solid State Disk (SSD)), etc. It should be noted that the computer-readable storage medium mentioned in the present application can be a non-volatile storage medium, in other words, it can be a non-transitory storage medium.

[0104] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above embodiments can be completed by hardware, or can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium, and the storage medium mentioned above can be a read-only memory, a magnetic disk, or an optical disc, etc.

[0105] In the description of the embodiments of the present application, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0106] In the description of the embodiments of the present application, unless otherwise specified, " / " means "or". For example, A / B may mean A or B. "And / or" herein is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone.

[0107] In the description of the embodiments of the present application, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, "a plurality of" means two or more.

[0108] The above are only exemplary embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A cloud real-time simulation calculation method, comprising: The front end receives a simulation request from a user; The cloud simulation service constructs initial full-scale simulation scenario data based on the simulation request, performs simulation calculations on the initial full-scale simulation scenario data to obtain an initial simulation result, and stores the initial full-scale simulation scenario data in memory; The cloud simulation service sends the initial simulation result to the front end; The front end receives a design scheme update instruction input by the user, calls the simulation data conversion service, and the simulation data conversion service converts the rendering material into a simulation material, constructs change data on the basis of the conversion, and sends the change data to the cloud simulation service; The cloud simulation service performs incremental data changes on the simulation scenario data in memory based on the change data to obtain changed simulation scenario data; Performs simulation calculations on the changed simulation scenario data to obtain a simulation result, and stores the changed simulation scenario data in memory; The cloud simulation service sends the simulation result to the front end.

2. The method according to claim 1, wherein, The performing simulation calculations on the changed simulation scenario data includes: The cloud simulation service loads the changed simulation scenario data, processes the changed simulation scenario data to obtain simulation intermediate data; The cloud simulation service analyzes and calculates the simulation intermediate data based on simulation parameters set by the user, and displays the results of the analysis and calculation in a low dynamic range image or a vector image.

3. The method according to claim 2, wherein The simulation intermediate data includes at least one of a high dynamic range image, a JSON file, and a channel map.

4. The method according to claim 1, further comprising: When the front end receives a stop simulation request from the user, or when no change request from the user is received within a preset threshold range, the changed simulation scenario data stored in memory is deleted.

5. A cloud real-time simulation calculation system, comprising: A front end, configured to receive a simulation request from a user; Receives a design scheme update instruction input by the user, generates change data based on the design scheme update instruction, and sends the change data to the cloud simulation service; A cloud simulation service, configured to construct initial full-scale simulation scenario data based on the simulation request, perform simulation calculations on the initial full-scale simulation scenario data to obtain an initial simulation result, and store the initial full-scale simulation scenario data in memory; sends the initial simulation result to the front end; Performs incremental data changes on the simulation scenario data in memory based on the change data to obtain changed simulation scenario data; Performs simulation calculations on the changed simulation scenario data to obtain a simulation result, and stores the changed simulation scenario data in memory; Sends the simulation result to the front end; Further comprising: A simulation data conversion service, configured to convert the rendering material into a simulation material based on the call of the front end, and construct the change data on the basis of the conversion.

6. The system according to claim 5, wherein, The cloud simulation service is used to load the changed simulation scenario data, process the changed simulation scenario data to obtain simulation intermediate data, and based on the simulation parameters set by the user, parse and calculate the simulation intermediate data, and display the results of the parsing and calculation in a low-dynamic range image or a vector map.

7. The system according to claim 6, wherein, The simulation intermediate data includes at least one of a high-dynamic range image, a JSON file, and a channel map.

8. The system according to claim 5, The cloud simulation service is further used to delete the changed simulation scenario data saved in the memory when the front end receives a user's simulation stop request or when no user change request is received within a preset threshold range.

9. An electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-4.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-4.

11. A computer program product, comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-4.

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