A mask pattern optimization method, program product, storage medium and device

Abstract

The present application relates to the field of computing lithography, in particular to a mask pattern optimization method, program product, storage medium and equipment; the method comprises: providing an intermediate mask pattern; detecting defects of the intermediate mask pattern to generate a database file, the database file containing a defect data group corresponding to each detected defect; real-time displaying the defect data group contained in the database file through a first graphical user interface; receiving a selection instruction for the defect data group in the first graphical user interface, recording the selected defect data group to a second graphical user interface and real-time displaying; continuing the iterative correction of the optical proximity effect, after each round of correction in the iteration process, updating the database file according to the newly corrected intermediate mask pattern. The method provides the function of quickly repositioning the previously positioned defect information for the staff, simplifies the operation steps of the user in the mask pattern correction process, and improves the work efficiency.

Description

[0001] The present application relates to the field of computing lithography, in particular to a mask pattern optimization method, program product, storage medium and device.

[0002] In the work of optical proximity correction, it is often necessary to detect and process defect information. When obtaining defect information, workers can often see a large amount of defect information. In the process of iterative lithography correction, workers need to repair specific defect positions and need to focus on the positions of the main defects.

[0003] Currently, defect information obtained by optical rule checking is usually recorded in a database, and workers can locate the defect information by searching in the database. However, for a larger layout, the database will become very large, and it is difficult to reposition the previously located defect information in the process of optical proximity correction iteration.

[0004] To solve the problem that it is difficult to reposition the previously located defect information in the process of existing optical proximity correction, the present application provides a mask pattern optimization method, program product, storage medium and device.

[0005] To solve the above technical problems, the present application provides the following technical solution: a mask pattern optimization method, the method comprising: providing an initial mask pattern, performing optical proximity correction on the initial mask pattern to obtain an intermediate mask pattern; detecting defects of the intermediate mask pattern to generate a database file, the database file containing a defect data group corresponding to each detected defect; displaying the defect data group contained in the database file in real time through a first graphical user interface; receiving a selection instruction for the defect data group in the first graphical user interface, recording the selected defect data group to a second graphical user interface and displaying it in real time; continuing the iterative correction of optical proximity correction, after each round of correction in the iteration process, updating the database file according to the newly corrected intermediate mask pattern; after completing the iterative correction, outputting the intermediate mask pattern obtained in the last iteration as an optimized mask pattern.

[0006] Preferably, the defect data group includes type information, position information and numerical information of the corresponding defect.

[0007] Preferably, the method further comprises: providing a third graphical user interface for displaying the intermediate mask pattern, receiving a selection instruction for the defect data group in the second graphical user interface; obtaining the position information of the corresponding defect from the selected defect data group, and displaying the corresponding defect in the third graphical user interface according to the obtained position information.​​​

[0008] Preferably, the first graphical user interface and the second graphical user interface both display the defect data set in a table form, the table in the first graphical user interface and the second graphical user interface has a filtering and sorting function, and the second graphical user interface further has a deletion function for the defect data set.

[0009] Preferably, the defect detection on the intermediate mask pattern is achieved by optical rule checking, and the optical rule checking is performed by providing a plurality of detectors, detection types and detection ranges to check the exposure profile of the intermediate mask pattern under different exposure conditions.

[0010] Preferably, the defect data set further comprises detector type information, detection range information and exposure condition information corresponding to the defect.

[0011] Preferably, when the iterative correction of the optical proximity effect is performed, only the defect corresponding to the defect data set displayed in the second graphical user interface is corrected.

[0012] To solve the above technical problems, the present application provides another technical solution as follows: a program product comprising computer programs / instructions, which, when executed by a processor, implement the steps of the mask pattern optimization method described above.

[0013] To solve the above technical problems, the present application provides another technical solution as follows: a storage medium having computer programs / instructions stored thereon, which, when executed by a processor, implement the steps of the mask pattern optimization method described above.

[0014] To solve the above technical problems, the present application provides another technical solution as follows: a computer device comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the mask pattern optimization method described above.

[0015] Compared with the prior art, the mask pattern optimization method, program product, storage medium and device provided by the present application have the following beneficial effects:

[0016] 1. The embodiment of the present application provides a mask pattern optimization method, which provides a first graphical user interface and a second graphical user interface to provide the staff with the function of quickly repositioning the previously positioned defect information, simplifies the operation steps of the user in the optical proximity correction process, and improves the work efficiency; specifically, an initial mask pattern is provided to provide a basis for subsequent optical proximity correction; the optical proximity correction on the initial mask pattern can reduce the deviation caused by the optical proximity effect, is beneficial to improve the accuracy of the mask pattern, detects the defects of the intermediate mask pattern, identifies the defects in the mask pattern, provides the basis for subsequent correction, can ensure that the defects are found and corrected in time, and improves the yield; the generation of the database file can systematically record the defect information, and facilitates the management and utilization of the defect information; the first graphical user interface is used for real-time display of the defect data group, an intuitive defect information display mode is provided, the user operation can be simplified, and the efficiency is improved; the second graphical user interface is used for recording and displaying the selected defect data group, and important defects can be conveniently paid attention to and tracked in the process of iterative correction of defects.

[0017] 2. In the embodiment of the present application, the type information, position information and numerical value information in the defect data group are displayed, comprehensive defect information is provided for the staff, and they are helped to more effectively perform defect management, positioning and repair work; specifically, the type information can help the staff to understand the nature of the defect, for example, edge position error, shrinkage or bridging defect, so as to better understand the causes and influences of the defects, and the repair methods of different types of defects may be different, and understanding the defect type is helpful for formulating a reasonable repair plan; the position information enables the staff to quickly locate the specific position where the defect occurs, facilitates detailed inspection and correction, and through the position information, the staff can track the changes of the defect in different correction rounds and evaluate the repair effect; the numerical value information can help the staff to quantify the severity of the defect, and the change of the numerical value information can be used to evaluate the effectiveness of the repair measures; in summary, by providing various types of defect information, the staff can more quickly identify and locate the problem, reduce invalid labor, and improve the repair efficiency.

[0018] 3. In the embodiment of the present application, the third graphical user interface is provided to display the intermediate mask pattern, the position of the selected defect is directly displayed on the third graphical user interface, the visualization effect of the defect information is enhanced, and the defect information is more intuitive and easy to understand; according to the selected defect data group in the second graphical user interface, the corresponding defect is positioned and displayed in the third graphical user interface, which can significantly improve the accuracy and efficiency of defect positioning; by automatically positioning and displaying the defect, the staff can quickly position and process the defect, and the overall work efficiency is improved, the automatic defect positioning reduces the errors that may occur when the staff searches for the defect, and the accuracy of defect management is improved.

[0019] 4. In the embodiments of the present application, the defect data set is displayed in the form of a table in the first and second graphical user interfaces. The table form makes the defect information clearer, reduces errors caused by information confusion, improves the readability of the information, and enables the user to conveniently browse and manage the defect information. The table has filtering and sorting functions. The filtering function enables the user to quickly find the defect types of interest, and the sorting function helps the user to sort the defects according to their severity or other indicators. The user can quickly locate the defect information of a specific type according to the needs, and the efficiency of processing the defect information is improved. The second graphical user interface also has a reduction function for the defect data set, which enables the user to conveniently remove the defect information that is no longer needed, and simplifies the management process of the defect information.

[0020] 5. In the embodiments of the present application, by providing multiple detectors, detection types, and detection ranges, comprehensive detection of the exposure profile of the reticle pattern under different exposure conditions can be achieved, and it is ensured that all types of defects are found. Specifically, by providing multiple detectors, different types of defects such as edge placement error, pinch, and bridging can be detected, and the comprehensiveness of the detection is improved. Appropriate detection types such as rule-based detection and model-based detection can be selected according to different detection needs, the flexibility of the detection is improved, and the detection process can better adapt to the diversified needs in actual production. Different detection ranges such as global detection and local detection can be set according to the needs, the pertinence of the detection is improved, and the detection process is more efficient. Different exposure conditions such as different exposure doses and focus offsets can be simulated to detect the performance of the reticle pattern under these conditions, and the authenticity and reliability of the detection are improved, and it is ensured that the performance of the reticle pattern in actual production meets the design requirements.

[0021] 6. In the embodiments of the present application, by displaying more detailed defect data sets, the judgment and work efficiency of the workers can be further improved. By providing detector type information, the workers can know which type of detector found the detected defects, which helps to more accurately judge the nature and cause of the defects. By providing detection range information, the workers can know in which area or range the defects were found, which helps to more accurately locate the position of the defects. By providing exposure condition information, the workers can know under which exposure condition the defects were found, which helps to analyze the cause of the defects and adjust the exposure conditions accordingly.

[0022] 7. In the embodiment of the present application, by only correcting the defects corresponding to the defect data set displayed in the second graphical user interface, it can be ensured that each iteration correction is based on the defects that need most attention, which helps to improve the pertinence of defect repair, ensures that each correction is valuable, and avoids excessive attention to non-critical defects, which helps to improve the efficiency of defect repair, reduce the time required for repairing defects, and speed up the process of mask pattern optimization.

[0023] 8. To solve the above technical problems, the embodiment of the present application also provides a program product comprising computer programs / instructions, which realize the steps of the mask pattern optimization method as described above when executed by a processor. The program product has the same beneficial effects as the above-mentioned mask pattern optimization method, which will not be repeated here.

[0024] 9. To solve the above technical problems, the embodiment of the present application also provides a storage medium having computer programs / instructions stored thereon, which realize the steps of the mask pattern optimization method as described above when executed by a processor. The storage medium has the same beneficial effects as the above-mentioned mask pattern optimization method, which will not be repeated here.

[0025] 10. To solve the above technical problems, the embodiment of the present application also provides a computer device comprising a memory, a processor and a computer program stored on the memory, wherein the processor executes the computer program to realize the steps of the mask pattern optimization method as described above. The computer device has the same beneficial effects as the above-mentioned mask pattern optimization method, which will not be repeated here.

DRAWINGS

[0026] Figure 1 is a flowchart of the mask pattern optimization method provided by the first embodiment of the present application.

[0027] Figure 2 is a flowchart of step S2 of the mask pattern optimization method provided by the first embodiment of the present application.

[0028] Figure 3 is a working state diagram of the mask pattern optimization method provided by the first embodiment of the present application.

[0029] Figure 4 is a table diagram displayed by the second graphical user interface in the mask pattern optimization method provided by the first embodiment of the present application.

[0030] Figure 5 is a block diagram of the program product provided by the second embodiment of the present application.

[0031] Figure 6 is a block diagram of the storage medium provided by the third embodiment of the present application.

[0032] Figure 7 is a block diagram of a computer device provided by a fourth embodiment of the present application.

[0033] The accompanying drawings are used to explain the present application:

[0034] 1, program product; 2, storage medium; 3, computer device.

DETAILED DESCRIPTION

[0035] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0036] In the embodiments provided by the present application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that the determination of B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0037] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in any suitable manner in one or more embodiments. Those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0038] In various embodiments of the present application, it should be understood that the size of the serial number of the above processes does not mean the inevitable sequence of execution order, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0039] The computer program product of the present application can have a signal, which can be recorded in a computer readable medium, to make a computer device execute procedures of the embodiments of the present application. The computer readable medium can include: a magnetic disk, an optical disc, a magnetic tape, a semiconductor memory, etc. The computer readable medium can be distributed to computer systems over a network, computer servers and storage devices, or be stored in the computer systems.

[0040] Referring to Figure 1 The first embodiment of the present application provides a mask layout optimization method, comprising the following steps:

[0041] S1: providing an initial mask layout, and performing optical proximity correction on the initial mask layout to obtain an intermediate mask layout;

[0042] S2: detecting defects of the intermediate mask layout to generate a database file, wherein the database file contains a defect data set corresponding to each detected defect;

[0043] S3: displaying the defect data set contained in the database file in real time through a first graphical user interface;

[0044] S4: receiving a selection instruction of the defect data set in the first graphical user interface, and recording the selected defect data set to a second graphical user interface and displaying in real time;

[0045] S5: continuing to perform iterative correction of the optical proximity effect, and updating the database file according to the intermediate mask layout obtained by the new correction after each round of correction in the iterative process is completed;

[0046] S6: outputting the intermediate mask layout obtained by the last iteration as an optimized mask layout after the iterative correction is completed.

[0047] It can be understood that the mask layout optimization method provided by the embodiment of the present application provides a first graphical user interface and a second graphical user interface, which can provide the staff with the function of quickly repositioning the previously positioned defect information, simplifies the operation steps of the user in the optical proximity correction process, and improves the work efficiency.

[0048] Specifically, the initial mask layout is provided to provide a basis for subsequent optical proximity correction; the optical proximity correction on the initial mask layout can reduce the deviation caused by the optical proximity effect, improve the accuracy of the mask layout, detect defects in the intermediate mask layout, identify defects in the mask layout, provide a basis for subsequent correction, and ensure that defects are discovered and corrected in a timely manner to improve the yield; the generation of the database file can systematically record defect information, facilitate the management and utilization of defect information; the first graphical user interface is used to display the defect data set in real time, provide an intuitive defect information display method, simplify user operation, and improve efficiency; the second graphical user interface is used to record and display the selected defect data set, which can facilitate the attention and tracking of important defects in the iterative defect correction process.

[0049] It should be noted that in step S1, the initial mask layout refers to the design layout before optical proximity correction (OPC). It is the starting point of the mask layout optimization process, and is usually created based on the designer's design intent and specification requirements. The initial mask layout contains all the necessary information of the chip design, which is used to guide the subsequent mask manufacturing process. Optical proximity correction, also known as OPC optimization, is a technology used to improve the quality of lithography in semiconductor manufacturing. It corrects the design layout in advance to compensate for pattern distortion caused by optical proximity effects in the lithography process.

[0050] As a feasible implementation, in step S2, the defect data set includes type information, position information and numerical information of the corresponding defect.

[0051] In the embodiment of the application, by displaying the type information, position information and numerical information in the defect data set, comprehensive defect information can be provided to the staff to help them more effectively manage, locate and repair defects; specifically, the type information can help the staff understand the nature of the defect, such as edge placement error, pinch or bridge connection, etc., so as to better understand the causes and effects of the defect, and different types of defects may have different repair methods, and understanding the defect type can help develop a reasonable repair plan; the position information enables the staff to quickly locate the specific position where the defect occurs, facilitating detailed inspection and correction, and through the position information, the staff can track the changes of the defect in different correction rounds to evaluate the repair effect; the numerical information can help the staff quantify the severity of the defect, and the change in numerical information can be used to evaluate the effectiveness of the repair measures; in summary, by providing multiple types of defect information, the staff can more quickly identify and locate problems, reduce ineffective labor, and improve repair efficiency.

[0052] As a feasible implementation, when performing step S2, the defect detection on the intermediate mask plate pattern is achieved by optical rule checking, and the exposure profile of the intermediate mask plate pattern under different exposure conditions is checked by providing various detectors, detection types and detection ranges.

[0053] It can be understood that, in the embodiments of the present application, by providing various detectors, detection types and detection ranges, comprehensive detection of the exposure profile of the mask plate pattern under different exposure conditions can be achieved, and all types of defects can be ensured to be found. Specifically, by providing various detectors, different types of defects such as EPE (edge position error), Pinch (pinch), Bridge (bridge) and the like can be detected, improving the comprehensiveness of the detection; appropriate detection types can be selected according to different detection requirements, such as rule-based detection, model-based detection and the like, improving the flexibility of the detection, so that the detection process can better adapt to the diversification requirements in actual production; different detection ranges can be set according to requirements, such as global detection, local detection and the like, improving the pertinence of the detection, so that the detection process is more efficient; different exposure conditions such as different exposure doses, focus offsets and the like can be simulated to detect the performance of the mask plate pattern under these conditions, improving the authenticity and reliability of the detection, and ensuring that the performance of the mask plate pattern in actual production meets the design requirements.

[0054] As a feasible implementation, the defect data set further includes detector type information, detection range information and exposure condition information corresponding to the defect.

[0055] It can be understood that, in the embodiments of the present application, by showing more detailed defect data sets, the judgment and work efficiency of the workers can be further improved; by providing detector type information, the workers can understand which type of detector found the detected defect, which helps to more accurately judge the nature and cause of the defect; by providing detection range information, the workers can understand in which area or range the defect was found, which helps to more accurately locate the position of the defect; by providing exposure condition information, the workers can understand under which exposure condition the defect was found, which helps to analyze the cause of the defect and adjust the exposure condition accordingly.

[0056] Please refer to Figure 4 , as a feasible implementation, Figure 4 The first column NO. of the table is a serial number column, the second and third columns are position information columns, X represents the horizontal coordinate, Y represents the vertical coordinate, Checker is a type information column, Size is a numerical information column, Range is a detection range information column, and Unit is a unit column. It can be understood that the display columns in the table can be increased or reduced according to requirements.

[0057] Please refer toFigure 2 As a feasible implementation, step S2 comprises the following steps:

[0058] Step S21: setting defect detection parameters; specifically including setting the detector type of the LRC tool, such as EPE (edge position error), Pinch (pinch), Bridge (bridge), etc.; setting the detection type and detection range, defining which types of defects need to be detected and the accuracy of detection. Determine different exposure conditions to check the reticle map under different exposure conditions.

[0059] Step S22: performing defect detection; specifically including using the LRC tool to perform defect detection on the intermediate reticle map, and scanning the reticle map according to the set detector type, detection type, detection range and exposure condition; it is beneficial to ensure that the detection process covers various possible defect types and achieves the required detection accuracy.

[0060] Step S23: collecting defect data and generating a defect data set; specifically including collecting the basic information of each detected defect, including but not limited to the type, position (X, Y coordinates), size, unit, detector name, detection type and detection range of the defect; integrating each defect information collected into a defect data set.

[0061] Step S24: constructing a database file. Specifically including creating a database file to store all defect data sets, and recording each defect data set into the database file.

[0062] It can be understood that this process realizes comprehensive and detailed defect detection on the intermediate reticle map, and organizes the detected defect information into an easy-to-manage and analyze form, aiming to provide key data support for subsequent reticle map optimization.

[0063] As a feasible implementation, in step S3, when the data in the database file changes, for example, after a new OPC correction is made, the user interface is automatically refreshed to ensure that the data displayed is up-to-date.

[0064] Please refer to Figure 3 and Figure 4 As a feasible implementation, the first graphical user interface and the second graphical user interface both display the defect data set in table form, and the tables in the first graphical user interface and the second graphical user interface have filtering and sorting functions, and the second graphical user interface also has a deletion function for the defect data set.

[0065] It can be understood that, in the embodiments of the present application, the defect data set is displayed in the form of a table in the first and second graphical user interfaces. The table form makes the defect information clearer, reduces errors caused by information confusion, improves the readability of the information, and enables the user to conveniently browse and manage the defect information. The table has a filtering and sorting function. The filtering function enables the user to quickly find the defect type of interest, and the sorting function helps the user to sort according to the severity of the defect or other indicators. The user can quickly locate the defect information of a specific type according to the need, thereby improving the efficiency of processing the defect information. The second graphical user interface also has a reduction function for the defect data set, so that the user can conveniently remove the defect information that is no longer needed, thereby simplifying the management process of the defect information.

[0066] As a feasible implementation, step S4 includes the following steps:

[0067] Step S41: receiving a selection instruction; specifically, the user selects one or more defect data sets in the first graphical user interface;

[0068] Step S42: transferring the information of the selected defect data set from the first graphical user interface to the second graphical user interface;

[0069] Step S43: parsing the incoming defect data set information in the second graphical user interface, and storing the information in the data structure of the second graphical user interface, such as a table or a list.

[0070] When step S4 is performed, the data display in the second graphical user interface is updated in real time to ensure that the user can see the latest selection results.

[0071] As a feasible implementation, the currently displayed defect data set can be exported as a file for further analysis or integration with other tools.

[0072] Please refer to Figure 3 As a feasible implementation, the mask pattern optimization method further includes: providing a third graphical user interface for displaying the intermediate mask pattern; receiving a selection instruction for the defect data set in the second graphical user interface; obtaining the position information of the corresponding defect from the selected defect data set, and displaying the corresponding defect in the third graphical user interface according to the obtained position information.

[0073] Understandably, in the embodiments of the present application, by providing a third graphical user interface for displaying the intermediate mask layout, the positions of the selected defects are directly displayed on the third graphical user interface, the visualization effect of the defect information is enhanced, and the defect information is more intuitive and easy to understand; according to the selected defect data group in the second graphical user interface, the corresponding defects are positioned and displayed in the third graphical user interface, which can significantly improve the accuracy and efficiency of defect positioning; by automatically positioning and displaying the defects, the worker can quickly position and process the defects, and the overall work efficiency is improved, and the automatic defect positioning reduces the errors that may occur when the defects are manually searched, and improves the accuracy of defect management.

[0074] As a feasible implementation manner, the first graphical user interface, the second graphical user interface and the third graphical user interface can be simultaneously displayed on the same display page.

[0075] As a feasible implementation manner, the table of the first graphical user interface prohibits deletion of data. Understandably, this design can ensure the integrity and accuracy of the original defect data, and avoid accidental deletion or modification of the data during processing.

[0076] As a feasible implementation manner, when the iterative correction of the optical proximity effect is performed, only the defects corresponding to the defect data group displayed in the second graphical user interface can be corrected.

[0077] Understandably, in the embodiments of the present application, by only correcting the defects corresponding to the defect data group displayed in the second graphical user interface, it can be ensured that each iteration correction is based on the defects that need to be paid attention to, which helps to improve the pertinence of defect repair, ensures that each correction is valuable, and avoids excessive attention to non-critical defects, which helps to improve the efficiency of defect repair, reduces the time required for repairing defects, and speeds up the process of mask layout optimization.

[0078] Please refer to Figure 5 To solve the above technical problems, a second embodiment of the present application provides another technical solution as follows: a program product 1 comprising computer programs / instructions, which, when executed by a processor, implement the steps of the mask layout optimization method described above. Understandably, the program product 1 has the same beneficial effects as the above-mentioned mask layout optimization method, which will not be repeated here.

[0079] Please refer to Figure 6To solve the above technical problems, the third embodiment of the present application provides another technical solution as follows: a storage medium 2, which stores a computer program / instruction, the computer program / instruction is executed by a processor to realize the steps of the mask layout optimization method as described above. It can be understood that the storage medium 2 has the same beneficial effects as the above-mentioned mask layout optimization method, which will not be repeated here.

[0080] Please refer to Figure 7 To solve the above technical problems, the fourth embodiment of the present application provides another technical solution as follows: a computer device 3, which includes a memory, a processor and a computer program stored in the memory, the processor executes the computer program to realize the steps of the mask layout optimization method as described above. It can be understood that the computer device 3 has the same beneficial effects as the above-mentioned mask layout optimization method, which will not be repeated here.

[0081] The above describes a mask layout optimization method, program product, storage medium and device disclosed by the embodiments of the present application in detail. The principles and implementation manners of the present application are described by applying specific examples in this paper. The above embodiment description is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manners and application ranges will be changed. In summary, the content of the specification should not be understood as a limitation of the present application. Any modification, equivalent replacement and improvement within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A mask layout optimization method, characterized in that, The method comprises: providing an initial mask layout, and performing optical proximity correction on the initial mask layout to obtain an intermediate mask layout; detecting defects of the intermediate mask layout to generate a database file containing defect data sets corresponding to each detected defect; displaying the defect data sets contained in the database file in real time through a first graphical user interface; receiving a selection instruction for the defect data sets in the first graphical user interface, recording the selected defect data sets to a second graphical user interface and displaying the selected defect data sets in real time; continuing the iterative correction of the optical proximity effect, and updating the database file according to the intermediate mask layout obtained after each round of correction in the iterative process; outputting the intermediate mask layout obtained after the last iteration as an optimized mask layout.

2. The mask pattern optimization method of claim 1, wherein: The defect data set comprises type information, position information and numerical information of the corresponding defect.

3. The mask pattern optimization method of claim 2, wherein, The method further comprises: providing a third graphical user interface for displaying the intermediate mask layout, and receiving a selection instruction for the defect data set in the second graphical user interface; obtaining the position information of the corresponding defect from the selected defect data set, and displaying the corresponding defect in the third graphical user interface according to the obtained position information.

4. The mask pattern optimization method of claim 1, wherein: The first graphical user interface and the second graphical user interface both display the defect data set in the form of a table, and the table in the first graphical user interface and the second graphical user interface has a filtering and sorting function, and the second graphical user interface further has a deletion function for the defect data set.

5. The mask layout optimization method of claim 1, wherein: the defect detection of the intermediate mask layout is achieved through optical rule checking, and the optical rule checking is performed by providing a plurality of detectors, detection types and detection ranges to check the exposure profile of the intermediate mask layout under different exposure conditions.

6. The mask pattern optimization method of claim 5, wherein: The defect data set further comprises detector type information, detection range information and exposure condition information of the corresponding defect.

7. The mask layout optimization method of claim 1, wherein: during the iterative correction of the optical proximity effect, only the defects corresponding to the defect data sets displayed in the second graphical user interface can be corrected.

8. A program product comprising computer programs / instructions, characterized in that: The computer program / instructions are executed by the processor to implement the steps of the mask layout optimization method of any one of claims 1-7.

9. A storage medium having stored thereon computer programs / instructions, characterized in that: The computer program / instructions are executed by the processor to implement the steps of the mask layout optimization method of any one of claims 1-7.

10. A computer device comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program comprises instructions that, when executed by the processor, cause the processor to perform the method of any one of claims 1-9. The processor executes the computer program to implement the steps of the mask layout optimization method of any one of claims 1-7. The processor executes the computer program to implement the steps of the mask layout optimization method of any one of claims 1-7.

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