Semiconductor SPC system data multi-thread rendering display device and method

Abstract

The invention provides a semiconductor SPC system data multi-thread rendering display device and method, and belongs to the field of semiconductor manufacturing, and the method specifically comprises the steps: obtaining sampling point data; displaying an interactive interface of the interactive operation to enable a user to select to-be-displayed interface content, and determining a rendering task according to the business operation corresponding to the selected interface content; performing service calculation on the sampling point data by adopting a multi-task concurrent mode, and outputting a task processing result; based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, determining a rendering mode of the task processing result, and generating a to-be-rendered result; decomposing the rendering task into a plurality of stage tasks of framing rendering based on the to-be-rendered result; and performing framing rendering on a task processing result according to the stage task, and displaying a rendered page. By means of the processing scheme, the mass semiconductor production data can be dynamically rendered, and efficient self-adaptive display of the mass semiconductor monitoring data is achieved.

Description

Technical Field

[0001] This application relates to the field of semiconductor intelligent manufacturing, and in particular to a semiconductor SPC system data multi-threaded rendering and display device and method. Background Technology

[0002] Semiconductor manufacturing processes generate massive amounts of production data. To control product quality, the production process needs to be monitored and controlled to ensure the products are in a stable state. Monitoring this massive amount of production data requires rendering it according to business needs. However, when rendering large volumes of data simultaneously, the rendering system is prone to lag. This not only increases rendering latency for display services but also prevents timely display of production data. Furthermore, in the event of a failure, monitoring alarms will be delayed. Therefore, how to avoid display lag and reduce rendering latency is a pressing issue that needs to be addressed. Summary of the Invention

[0003] Therefore, in order to overcome the shortcomings of the prior art, the present invention provides a semiconductor SPC system data multi-threaded rendering and display device and method that can dynamically render massive amounts of semiconductor production data and realize efficient adaptive display of massive amounts of semiconductor monitoring data.

[0004] To achieve the above objectives, the present invention provides a semiconductor SPC system data multi-threaded rendering and display device, comprising: an acquisition module for acquiring sampling point data, the sampling point data including at least process parameters, measured values, and batch information; a user interaction module for displaying an interactive interface for allowing the user to select interface content to be displayed, and then determining a rendering task based on the business operation corresponding to the selected interface content; an asynchronous computing module for constructing a WebWorker thread pool, performing business calculations on the sampling point data in a multi-task concurrent mode, and outputting task processing results; a rendering engine module for determining the rendering mode for the task processing results based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, and generating a result to be rendered; a rendering scheduling module for decomposing the rendering task into multiple frame-by-frame rendering stage tasks based on the result to be rendered; and an image display module for performing frame-by-frame rendering of the task processing results according to the stage tasks and displaying the rendered page.

[0005] In one embodiment, the rendering engine module includes: a rendering strategy control unit, which generates a rendering strategy to be output to the corresponding rendering unit based on the data volume of the sampling point data, the business operation corresponding to the selected interface content, and the graphics capabilities of the display terminal; a 2D rendering unit, which processes the task processing result into a planar image according to the rendering strategy; a 3D rendering unit, which processes the task processing result into a three-dimensional spatial image according to the rendering strategy; and a hybrid rendering unit, which combines and superimposes the planar image and the three-dimensional spatial image according to the rendering strategy to form a multi-layered superimposed display image.

[0006] In one embodiment, the hybrid rendering unit includes: a 3D scene rendering subunit for generating a three-dimensional rendering scene; a 2D interactive element subunit for generating two-dimensional interactive elements; and a composite rendering subunit for overlaying the content of the two-dimensional interactive elements onto the three-dimensional rendering scene to form an overlaid display image.

[0007] In one embodiment, the asynchronous computing module includes: a thread pool construction unit, used to construct a task queue based on the business operations to be run and pre-established Worker instances to form a Web Worker thread pool; a thread pool management unit, used to allocate and schedule each task in the task queue through the main thread and Worker threads; and a resource management unit, used to monitor each Worker thread that allocates tasks and allocate or reclaim Worker instances.

[0008] In one embodiment, the asynchronous computing module further includes: an anomaly detection unit, used to analyze the sampling point data based on the execution rule engine and identify sampling anomalies; a data filtering unit, used to filter data within a user-specified range according to the business operation to be run, and allocate it to the main thread or worker thread for calculation; and a trend analysis unit, used to calculate trend lines and abrupt change analysis based on the historical data and current data corresponding to the sampling points.

[0009] In one embodiment, the rendering scheduling module includes: a task splitting unit, used to split the rendering task into multiple stage tasks; and a rendering queue control unit, used to dynamically adjust the scheduling order of the stage tasks according to the display priority of the business operation corresponding to the selected interface content, the visibility and interaction status on the rendering page, and generate a rendering queue allocated to the image display module.

[0010] In one embodiment, the rendering scheduling module further includes a task scheduling and merging unit, which is used to merge all the state updates within a predetermined time period when it is determined that the frequency of state updates of the chart corresponding to the rendering page exceeds a preset threshold within a predetermined time period, and centrally generate a rendering scheduling queue.

[0011] A method for multi-threaded rendering and displaying data in a semiconductor SPC system includes: acquiring sampling point data, wherein the sampling point data includes at least process parameters, measured values, and batch information; displaying an interactive interface for user selection of interface content to be displayed, and then determining a rendering task based on the business operation corresponding to the selected interface content; constructing a WebWorker thread pool, performing business calculations on the sampling point data in a multi-task concurrent mode, and outputting task processing results; determining the rendering mode for the task processing results based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, and generating a result to be rendered; decomposing the rendering task into multiple frame-by-frame rendering stages based on the result to be rendered; performing frame-by-frame rendering on the task processing results according to the stage tasks, and displaying the rendered page.

[0012] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the method described above.

[0013] A computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the above-described method.

[0014] Compared with existing technologies, the advantages of this invention are as follows: it not only determines the rendering mode of dynamic rendering by the amount of data of sampling points, realizing efficient adaptive display of massive semiconductor SPC data; but also decomposes the rendering task into multiple frame-by-frame rendering stage tasks and combines frame-by-frame rendering technology to realize real-time high-performance charts and business linkage, significantly improving quality control efficiency; and adopts a multi-task concurrent mode to perform business calculations on sampling point data and output task processing results, improving the asynchronous processing capability of anomaly detection and ensuring smooth interaction. The entire solution adjusts from multiple dimensions to avoid rendering stuttering during the display process and also reduces rendering latency. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a structural block diagram of the device for efficiently rendering and displaying semiconductor monitoring data in an embodiment of the present invention; Figure 2 This is a flowchart illustrating a method for efficiently rendering and displaying semiconductor monitoring data in one embodiment of the present invention; Figure 3 This is an internal structural diagram of a computer device according to one embodiment of the present invention. Detailed Implementation

[0017] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0018] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] It should be noted that the following description covers various aspects of embodiments within the scope of protection of this invention. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice apparatus. Additionally, this device and / or practice apparatus can be implemented using other structures and / or functionalities besides one or more of the aspects set forth herein.

[0020] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0021] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0022] This application provides an apparatus for efficiently rendering and displaying semiconductor monitoring data, which can be combined with a server or a terminal. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable smart devices. The server can be a standalone server or a server cluster composed of multiple servers.

[0023] A semiconductor SPC (Statistical Process Control) system is a system that monitors and manages the semiconductor manufacturing process using statistical techniques. SPC is a quality control method based on statistical principles. It collects, analyzes, and monitors data on key quality characteristics during production, promptly identifies abnormal fluctuations in the process, and takes corresponding corrective measures, thereby achieving effective control of the production process and improving product quality and production efficiency. SPC systems use statistical tools such as control charts to compare collected process data with control limits, thus distinguishing between normal and abnormal variations. When data points exceed control limits, it indicates an anomaly in the process, requiring timely adjustments.

[0024] In one embodiment, such as Figure 1 As shown, a semiconductor SPC system data multi-threaded rendering and display device is provided. The device is combined with a user-held terminal and includes an acquisition module 101, a user interaction module 102, an asynchronous computing module 103, a rendering engine module 104, a rendering scheduling module 105, and an image display module 106.

[0025] The acquisition module 101 is used to acquire sampling point data, which includes at least process parameters, measured values, and batch information. The sampling point data can be data corresponding to and related to physical sampling points, obtained from semiconductor manufacturing equipment and / or monitoring systems. A physical sampling point is the geographical location of the sampled equipment within a semiconductor factory, possessing uniqueness and determinism. The sampling point data can include process parameters, measured values, and batch information. In some embodiments, the sampling point data can also include time information, special process information, etc. The terminal can control the acquisition module 101 to acquire sampling point data from a cloud database, semiconductor manufacturing equipment, or monitoring system. In one embodiment, the acquisition module 101 further includes a preprocessing unit, which can perform standardized preprocessing on the sampling point data. The data output by the acquisition module 101 can be a standardized structured data set. The acquisition module 101 can transmit the (preprocessed) sampling point data to the asynchronous computing module 103 and the rendering engine module 104.

[0026] The user interaction module 102 displays an interactive interface for user operations, allowing users to select the content to be displayed. The rendering task is then determined based on the business operation corresponding to the selected content. The terminal displays the interactive interface through the user interaction module, allowing users to select the content to be displayed. Users can adjust the interface content corresponding to the desired business operation through box selection, point selection, and other interactive operations. The terminal can determine the corresponding business operation based on the interface content and obtain the corresponding sampling point data based on the business operation, then transmit the corresponding business analysis logic to the asynchronous computing module 103. The user interaction module 102 can feed back the interactive command carrying the selected interface content to the asynchronous computing module 103 and the rendering engine module 104, driving dynamic updates of charts and display of business information.

[0027] The asynchronous computation module 103 is used to construct a Web Worker thread pool, employing a multi-task concurrent mode to perform business calculations on the sampled point data and output the task processing results. The asynchronous computation module 103 is responsible for complex computation tasks, including anomaly detection, data filtering, and trend analysis. Based on the Web Worker thread pool, the asynchronous computation module 103 supports multi-task concurrency, priority scheduling, and result caching. The input data for the asynchronous computation module 103 can be the raw sampled point data and / or preprocessed data passed from the acquisition module 101, and the interaction commands from the user interaction module 102. The asynchronous computation module 103 can output the computation results to the rendering engine module 104, triggering chart updates; it also outputs analysis results for the user interaction module 102 to access.

[0028] The rendering engine module 104 is used to determine the rendering mode for the task processing results based on the data volume of the sampling point data and the business operations corresponding to the selected interface content, and to generate the rendering result. The rendering engine module 104 can visualize SPC charts (monitoring charts) based on the data volume of the sampling point data and the business operations corresponding to the selected interface content. The terminal can select either two-dimensional or three-dimensional rendering mode as needed. Specifically, when the terminal can select WebGL rendering and / or Canvas rendering, the terminal will determine whether the data volume is lower than a first preset threshold or whether the terminal supports WebGL rendering. If either determination is negative, the terminal will only use Canvas rendering. If the terminal determines that the data volume is between the first and second preset thresholds, the terminal determines that a hybrid rendering mode is satisfied: a dynamic rendering strategy is adopted, switching between Canvas rendering and GPU WebGL rendering according to the data scale, supporting multi-layer overlay. If the terminal determines that the data volume is greater than the second preset threshold, the terminal determines that the WebGL rendering enable condition is satisfied, and only GPU WebGL rendering is used. The first and second preset thresholds are determined based on the terminal's computing memory, and the first and second preset thresholds may be different for different terminals. The input data for the rendering engine module 104 can be structured data passed in by the acquisition module; the output data can be rendering instructions and graphic display results for use by the user interaction module.

[0029] The rendering scheduling module 105 is used to decompose the rendering task into multiple frame-by-frame rendering stages based on the result to be rendered. The rendering scheduling module 105 can control the frame-by-frame execution of the rendering task, avoiding main thread blocking and ensuring smooth rendering and interaction. For example, the rendering scheduling module 105 can break down the complete rendering process of a single chart into multiple stages, such as initialization, data binding, layout calculation and drawing, etc., and advance them step by step frame by frame, avoiding long-term main thread blocking and improving page smoothness. The data input to the rendering scheduling module 105 can be the rendering tasks and data from the rendering engine module; the rendering scheduling module 105 can output frame-by-frame rendering instructions to the image display module 106.

[0030] The image display module 106 is used to render the task processing results frame by frame according to the stage task and display the rendered page. The image display module 106 receives the frame-by-frame rendering instructions from the rendering scheduling module 105 and displays the rendered page according to the frame-by-frame rendering instructions.

[0031] In one embodiment, the user interaction module 102 and the image display module 106 may be the same display module or different display modules located on the terminal.

[0032] The aforementioned device not only determines the dynamic rendering mode based on the data volume of sampling points, achieving efficient and adaptive display of massive semiconductor SPC data, but also decomposes the rendering task into multiple frame-based rendering stages. Combined with frame-based rendering technology, it achieves real-time high-performance charts and business linkage, significantly improving quality control efficiency. Furthermore, it employs a multi-task concurrent mode to perform business calculations on the sampling point data and output task processing results, enhancing asynchronous anomaly detection capabilities and ensuring smooth interaction. The entire solution adjusts from multiple dimensions to avoid rendering stuttering during the display process and reduces rendering latency. Moreover, the device, through a data acquisition module, rendering engine module, asynchronous calculation module, rendering scheduling module, and user interaction module, respectively acquires semiconductor production sampling point data and process parameters, dynamically switches rendering engines based on data scale for high-performance chart drawing, achieves anomaly detection and data filtering through multi-threaded asynchronous calculation, utilizes a frame-based mechanism to ensure smooth rendering, and supports multi-dimensional interaction and business data linkage, thereby significantly improving the real-time visualization efficiency and anomaly analysis capabilities of massive data in the semiconductor SPC system.

[0033] In one embodiment, the rendering engine module includes a rendering strategy control unit, a 2D rendering unit, a 3D rendering unit, and a hybrid rendering unit.

[0034] The rendering strategy control unit generates a rendering strategy for the corresponding rendering unit based on the data volume of the sampled points, the business operation corresponding to the selected interface content, and the graphics capabilities of the display terminal. The terminal can automatically determine the rendering mode based on the data volume, interaction complexity, and the terminal's graphics capabilities. The input data to the rendering strategy control unit can be preprocessed data volume indicators; the output data can be rendering engine switching instructions passed to specific rendering units.

[0035] The 2D rendering unit processes task results into planar images according to a rendering strategy. In one embodiment, 2D rendering can be Canvas rendering. The 2D rendering unit efficiently draws small-scale data, completes the drawing of auxiliary graphics (axis lines, scales, grid lines, and label text, etc.) and interactive feedback layers (capturing user interaction events using the Canvas layer and mapping the interactive feedback to the WebGL rendering area), and handles low-frequency interactions and high-precision drawing. The input data for the 2D rendering unit are sampling point data and rendering engine switching instructions from the rendering strategy control unit; the output data can be the Canvas graphics rendering result.

[0036] A 3D rendering unit is used to process the task processing results into a three-dimensional spatial image according to a rendering strategy. In one embodiment, 3D rendering can be GPU WebGL rendering. The 3D rendering unit can be responsible for high-performance rendering and updating of large-scale primitives, drawing high-density data points, such as scatter plots, in WebGL layers. The input data of the 3D rendering unit can be sampling point data and rendering engine switching instructions from the rendering strategy control unit. The output data can be the GPU-rendered graphics result.

[0037] The hybrid rendering unit is used to combine and overlay 2D and 3D spatial images according to a rendering strategy, forming a multi-layered overlay display image. The hybrid rendering unit can be responsible for combining the Canvas and GPU rendering results to achieve multi-layered overlay display. Input data can be the output graphics of the Canvas and GPU rendering units. Output data can be a composite layer displayed to the user interaction module.

[0038] The aforementioned device achieves adaptive optimization of chart performance under different data scales by employing a Canvas and GPU fusion rendering mechanism.

[0039] In one embodiment, the hybrid rendering unit includes: a 3D scene rendering subunit for generating a 3D rendering scene; a 2D interactive element subunit for generating 2D interactive elements; and a composite rendering subunit for overlaying the content of the 2D interactive elements onto the 3D rendering scene to form an overlaid display image.

[0040] The 3D scene rendering subunit can create a WebGL context and render a 3D scene.

[0041] The 2D interactive element sub-unit can create a Canvas 2D context and draw 2D content as a two-dimensional interactive element.

[0042] The compositing rendering subunit can use the gl.texImage2D function to bind Canvas 2D content to a WebGL texture, and use drawArraysInstanced to render multiple Canvas 2D texture instances in WebGL.

[0043] The aforementioned device binds 2D content as textures to a 3D rendering scene and renders multiple instances, thereby achieving more complex blending effects.

[0044] In one embodiment, the asynchronous computing module includes a thread pool construction unit, a thread pool management unit, and a resource management unit.

[0045] The thread pool building unit is used to construct a task queue based on the business operations to be run and pre-established Worker instances, forming a Web Worker thread pool. When a task needs to be executed, the terminal can retrieve the task from the task queue and assign it to an idle Worker.

[0046] The thread pool management unit is used to allocate and schedule tasks in the task queue through the main thread and worker threads. The thread pool management unit can use `postMessage` and `onMessage` to facilitate communication between the main thread and the worker threads.

[0047] The resource management unit is used to monitor the worker threads that assign tasks, and to allocate or reclaim worker instances. The resource management unit can use Promises to manage the completion status of tasks. After a task is completed, the resource management unit waits for the result via callback or synchronous execution.

[0048] The aforementioned device, by employing an asynchronous computing mechanism using a thread pool, achieves non-blocking processing of SPC big data computing tasks and multi-chart concurrency optimization.

[0049] In one embodiment, the asynchronous computing module further includes an anomaly detection unit, a data filtering unit, and a trend analysis unit.

[0050] The anomaly detection unit analyzes the sampled point data based on the execution rule engine to identify sampling anomalies. The anomaly detection unit analyzes the sampled point data based on the input execution rule engine to identify sampling anomalies and / or abrupt change trends. Input data can be sampled point data and interactive commands output by the user interaction module 102. Output data can be a list of anomalies for use by the rendering engine module and the image display module.

[0051] The data filtering unit is used to filter data within a user-specified range based on the business operation to be run, and then allocate the data to the main thread or worker thread for calculation. The data filtering unit can perform data filtering and aggregation calculations within a user-specified range. Input data can be sampling point data and interactive commands output by the user interaction module 102. Output data can be the filtered subset of data fed back to the image display module.

[0052] The trend analysis unit is used to calculate trend lines and perform abrupt change analysis based on historical and current data corresponding to the sampling points. The input data can be historical and current data based on the sampling points. The output data can be trend line data and analysis results that drive chart creation and business decisions.

[0053] In one embodiment, the rendering scheduling module includes a task splitting unit and a rendering queue control unit.

[0054] The task splitting unit is used to break down the rendering task into multiple stages. The task splitting unit divides the complete rendering process of a single chart into multiple stages, such as initialization, data binding, layout calculation and drawing, progressing step-by-step frame by frame, avoiding long-term blocking of the main thread and improving page smoothness.

[0055] The rendering queue control unit dynamically adjusts the scheduling order of stage tasks based on the display priority of the business operations corresponding to the selected interface content, as well as the visibility and interaction status on the rendering page, generating rendering queues allocated to the image display module. The rendering queue control unit dynamically adjusts the scheduling order of rendering tasks based on the priority, visibility, and interaction status of the charts, and limits the number of charts rendered simultaneously, thereby preventing page lag or crashes when there are many charts.

[0056] The aforementioned device achieves a smooth user experience even during data updates or chart interactions by employing a frame-by-frame rendering control mechanism.

[0057] In one embodiment, the rendering scheduling module further includes a task scheduling and merging unit.

[0058] The task scheduling and merging unit is used to merge all state updates within a predetermined time period when the frequency of state updates of the corresponding chart on the rendering page exceeds a preset threshold, and centrally generate a rendering scheduling queue. When the task scheduling and merging unit detects frequent state updates (such as scaling, filtering, or linkage) of multiple charts, it merges the high-frequency updates within a short period of time and centrally schedules rendering using mechanisms such as requestAnimationFrame to avoid invalid duplicate drawing.

[0059] The aforementioned device, through the two-way linkage between chart interaction and business data, realizes an integrated closed loop for SPC visual analysis, from "viewing charts" to "making decisions".

[0060] In one embodiment, such as Figure 2 As shown, a method for multi-threaded rendering and displaying data in a semiconductor SPC system is provided. Taking the application of this method to a terminal as an example, the method includes the following steps: Step 201: Obtain sampling point data. The sampling point data shall include at least process parameters, measured values ​​and batch information.

[0061] Step 202: Display the interactive interface for interactive operations, allowing the user to select the interface content to be displayed, and then determine the rendering task based on the business operation corresponding to the selected interface content.

[0062] Step 203: Construct a Web Worker thread pool, use a multi-task concurrent mode to perform business calculations on the sampled data, and output the task processing results.

[0063] Step 204: Based on the amount of data from the sampling points and the business operations corresponding to the selected interface content, determine the rendering mode for the task processing results and generate the results to be rendered.

[0064] Step 205: Based on the result to be rendered, the rendering task is decomposed into multiple frame-by-frame rendering stages.

[0065] Step 206: Render the task processing results in frames according to the stage tasks, and display the rendered page.

[0066] Specific limitations regarding the method for efficient rendering and display of semiconductor monitoring data can be found in the limitations of the device for efficient rendering and display of semiconductor monitoring data described above, and will not be repeated here. Each module in the aforementioned device for efficient rendering and display of semiconductor monitoring data can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0067] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for efficiently rendering and displaying semiconductor monitoring data. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0068] Those skilled in the art will understand that Figure 3The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0069] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring sampling point data, the sampling point data including at least process parameters, measured values, and batch information; displaying an interactive interface for interactive operations, allowing the user to select interface content to be displayed, and then determining a rendering task based on the business operation corresponding to the selected interface content; constructing a Web Worker thread pool, performing business calculations on the sampling point data in a multi-task concurrent mode, and outputting task processing results; determining the rendering mode for the task processing results based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, and generating a result to be rendered; decomposing the rendering task into multiple frame-by-frame rendering stage tasks based on the result to be rendered; performing frame-by-frame rendering on the task processing results according to the stage tasks, and displaying the rendered page.

[0070] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program performs the following steps: acquiring sampling point data, the sampling point data including at least process parameters, measured values, and batch information; displaying an interactive interface for interactive operations, allowing the user to select interface content to be displayed, and then determining a rendering task based on the business operation corresponding to the selected interface content; constructing a Web Worker thread pool, performing business calculations on the sampling point data in a multi-task concurrent mode, and outputting task processing results; determining the rendering mode for the task processing results based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, and generating a result to be rendered; decomposing the rendering task into multiple frame-by-frame rendering stage tasks based on the result to be rendered; performing frame-by-frame rendering of the task processing results according to the stage tasks, and displaying the rendered page.

[0071] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A semiconductor SPC system data multi-threaded rendering and display device, characterized in that, include: The acquisition module is used to acquire sampling point data, which includes at least process parameters, measured values, and batch information. The user interaction module is used to display the interactive interface for interactive operations, allowing users to select the interface content to be displayed, and then determining the rendering task based on the business operation corresponding to the selected interface content. The asynchronous computing module is used to build a Web Worker thread pool, perform business calculations on the sampled data in a multi-task concurrent mode, and output the task processing results. The rendering engine module is used to determine the rendering mode of the task processing result based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, and to generate the result to be rendered. The rendering scheduling module is used to decompose the rendering task into multiple frame-by-frame rendering stage tasks based on the result to be rendered. The image display module is used to render the task processing results in frames according to the stage task and display the rendered page.

2. The apparatus according to claim 1, characterized in that, The rendering engine module includes: The rendering strategy control unit generates a rendering strategy to be output to the corresponding rendering unit based on the amount of data of the sampling point data, the business operation corresponding to the selected interface content, and the graphics capabilities of the display terminal. A 2D rendering unit is used to process the task processing results into a planar image according to the rendering strategy. The 3D rendering unit is used to process the task processing results into a three-dimensional spatial image according to the rendering strategy. The hybrid rendering unit is used to combine and overlay the planar image and the three-dimensional spatial image according to the rendering strategy to form a multi-layered overlay display image.

3. The apparatus according to claim 2, characterized in that, The hybrid rendering unit includes: The 3D scene rendering subunit is used to generate 3D rendered scenes. 2D interactive element subunit, used to generate two-dimensional interactive elements; The composite rendering subunit is used to overlay the content of two-dimensional interactive elements onto a three-dimensional rendering scene to form an overlay display image.

4. The apparatus according to claim 1, characterized in that, The asynchronous computing module includes: The thread pool construction unit is used to build a task queue based on the business operations to be run and the pre-established Worker instances, forming a Web Worker thread pool; The thread pool management unit is used to allocate and schedule tasks in the task queue through the main thread and worker threads; The resource management unit is used to monitor each Worker thread that assigns tasks, and to allocate or reclaim Worker instances.

5. The apparatus according to claim 4, characterized in that, The asynchronous computing module also includes: An anomaly detection unit is used to analyze the sampling point data based on the execution rule engine and identify sampling anomalies; The data filtering unit is used to filter data within a range specified by the user according to the business operation to be run, so as to allocate it to the main thread or worker thread for calculation; The trend analysis unit is used to calculate trend lines and perform abrupt change analysis based on historical and current data corresponding to the sampling points.

6. The apparatus according to claim 1, characterized in that, The rendering scheduling module includes: The task splitting unit is used to split the rendering task into multiple stage tasks; The rendering queue control unit is used to dynamically adjust the scheduling order of the stage tasks according to the display priority of the business operation corresponding to the selected interface content, the visibility and interaction status on the rendering page, and generate a rendering queue to be allocated to the image display module.

7. The apparatus according to claim 6, characterized in that, The rendering scheduling module also includes: The task scheduling and merging unit is used to merge all the state updates within a predetermined time period when it is determined that the frequency of state updates of the chart corresponding to the rendering page exceeds a preset threshold within a predetermined time period, and centrally generate a rendering scheduling queue.

8. A method for multi-threaded rendering and displaying data in a semiconductor SPC system, characterized in that, include: Acquire sampling point data, which includes at least process parameters, measured values, and batch information; The interactive interface displays interactive operations, allowing users to select the interface content to be displayed, and then determines the rendering task based on the business operation corresponding to the selected interface content. Construct a Web Worker thread pool, use a multi-task concurrent mode to perform business calculations on the sampled data, and output the task processing results; Based on the data volume of the sampling point data and the business operation corresponding to the selected interface content, the rendering mode for the task processing result is determined, and the result to be rendered is generated. Based on the result to be rendered, the rendering task is decomposed into multiple frame-by-frame rendering stage tasks. The task processing results are rendered in frames according to the stage tasks, and the rendered page is then displayed.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method of claim 8.

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