A simulation bad point repair method, system and storage medium

Abstract

The present invention relates to the field of photolithography technology, and in particular to a simulation bad point repair method, system and storage medium. The simulation bad point repair method of the present invention comprises the following steps: providing an initial layout after optical proximity correction, performing photolithography simulation inspection on the initial layout, locating the simulation bad point position and the variable area of ​​the preset range corresponding to the bad point; obtaining the graphics at the coordinates of all simulation bad points, and classifying the graphics based on preset standards; selecting a classification representative from each classification, bringing the simulation bad point and the corresponding variable area represented by the classification into the repair process for repair; obtaining the repaired classification representative and the corresponding variable area, replacing all the simulation bad points and variable areas of the same type in the repaired layout, and obtaining the replaced layout; outputting the replaced layout as the required layout. Select the bad point and the corresponding variable area classification, select the classification representative to substitute for the repair, replace other wholes of the same type, the repair is more comprehensive, and the repair time is reduced.

Description

[Technical field]

[0001] The present invention relates to the field of photolithography technology, and in particular to a simulation bad point repair method, system and storage medium. [Background technology]

[0002] In the manufacturing process of integrated circuits, the chip factory (FAB) needs to obtain the optical proximity correction (OPC) mask data (Mask) from the original design pattern, and then take the mask data to tape-out. However, in actual industrial practice, it is difficult to achieve universality without blind spots in lithography image correction, and it is impossible to get good results for all design patterns. Therefore, in practice, for the layout optimized by lithography image correction, after lithography simulation detection (LRC), there will still be simulated bad points, so lithography simulation bad point repair (Mask Repair) technology is needed. That is, local targeted treatment is performed on lithography simulation bad points to repair the bad points.

[0003] However, there is an obvious problem: although the cutting edge is definitely related to the bad pixel, perhaps other surrounding cutting edges are the main cause. Continuously modifying this cutting edge may be counterproductive and cannot effectively solve the current bad pixel. Moreover, if the mask error enhancement factor (MEEF) at the bad pixel is relatively large, it is necessary to make larger changes to the local area to have an effect, which can easily cause the minimum resolvable contrast and unreasonable mask graphics, and even affect other locations and produce new bad pixels. [Summary of the invention]

[0004] In order to repair lithography simulated bad spots in a more comprehensive and systematic manner, the present invention provides a simulated bad spot repair method, system and storage medium.

[0005] The solution to the technical problem of the present invention is to provide a method for repairing simulated bad spots, comprising the following steps: providing an initial layout after optical proximity correction, performing lithography simulation inspection on the initial layout, locating the position of the simulated bad spot and the variable area of ​​a preset range corresponding to the bad spot; obtaining graphics at the coordinates of all simulated bad spots, and classifying the graphics based on preset standards; selecting a classification representative from each classification, placing contour evaluation points at the coordinates of the simulated bad spots of the classification representative to form a contour evaluation index, and bringing the simulated bad spots and the corresponding variable areas of the classification representative into the repair process for progressive repair, wherein the repair process uses a multivariable optimization function to repair simulated bad spots, and generates a penalty item of the multivariable optimization function based on the contour evaluation index; obtaining the repaired classification representative and the corresponding variable area, replacing all simulated bad spots and variable areas of the same type in the repaired layout, and obtaining the replaced layout; and outputting the replaced layout as the required layout.

[0006] Preferably, the variable region is a rectangular region.

[0007] Preferably, graphics at the coordinates of all simulated bad spots are obtained, and graphics classification based on preset standards includes graphics matching and classification according to the geometric properties of the simulated bad spots, which specifically includes the following steps: obtaining all geometric graphics at the coordinates of the simulated bad spots and classifying them, defining a preset repair strategy for each type; obtaining the corresponding geometric graphic type for each simulated bad spot, and selecting the corresponding preset repair strategy.

[0008] Preferably, the variable region includes an optimized variable region surrounding the simulation bad point and a fixed variable region surrounding the optimized variable region.

[0009] Preferably, a classification representative is selected from each classification and brought into the simulation bad pixel repair process of the initial layout for progressive repair, including the following steps: initial optimization is performed based on the simulation bad pixels and corresponding optimization variable areas in the selected classification representative; it is determined whether the layout after the initial optimization has been repaired; if the repair is completed, the repair process is exited; if the repair is not completed, the above initial optimization process for the selected classification representative is iterated until the simulation bad pixels are completely repaired and the repair process is exited.

[0010] Preferably, before the initial optimization is performed based on the simulated bad points and the corresponding variable areas in the selected classification representatives, the following steps are also included: based on the selected classification representatives, a contour line evaluation index is placed at the coordinates of the simulated bad points in a preset placement manner; it is determined whether the contour of the figure at the coordinates of the simulated bad points is within the contour line evaluation index; if the contour of the figure at the coordinates of the simulated bad points is within the contour line evaluation index, it is determined that the contour of the figure has no effect on the multivariable optimization function; if the contour of the figure at the coordinates of the simulated bad points is outside the contour line evaluation index, a penalty item is set in the multivariable optimization function.

[0011] Preferably, placing the contour line evaluation index at the simulated bad point coordinates in a preset placement manner based on the selected classification representative specifically includes the following steps: based on the selected classification representative, placing two contour line evaluation points based on the inside and outside of the geometric figure at the simulated bad point coordinates according to the specifications of the lithography simulation detection inspection; the gap area between the two contour line evaluation points constitutes a contour line evaluation index.

[0012] In order to solve the above technical problems, the present invention also provides a simulation bad pixel repair system, which implements the simulation bad pixel repair method as described above, including an information acquisition module: used to obtain the simulation bad pixel position in the initial layout after lithography simulation inspection and the variable area of ​​a preset range corresponding to the bad pixel, and obtain the graphics at the coordinates of all simulation bad pixels; a graphic classification and screening module: classify the graphics at the coordinates of the simulation bad pixels based on preset standards, and select a classification representative from each classification; a layout extraction and replacement module: extract the simulation bad pixels and corresponding variable areas of all classification representatives, obtain the repaired classification representatives and corresponding variable areas, and replace all the simulation bad pixels and variable areas of the same type in the repaired layout.

[0013] To solve the above technical problems, the present invention also provides a storage medium, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the simulated bad pixel repair method as described above is implemented.

[0014] Compared with the prior art, the simulated bad pixel repair method, system and storage medium of the present invention have the following advantages:

[0015] 1. The simulation bad point repair method of the present invention includes the following steps: providing an initial layout after optical proximity correction, performing lithography simulation inspection on the initial layout, locating the simulation bad point position and the variable area of ​​the preset range corresponding to the bad point; obtaining the graphics at the coordinates of all simulation bad points, and classifying the graphics based on the preset standard; selecting a classification representative from each classification, bringing the simulation bad point and the corresponding variable area represented by the classification into the repair process for progressive repair; obtaining the repaired classification representative and the corresponding variable area, replacing all the simulation bad points and variable areas of the same type in the repaired layout, and obtaining the replaced layout; outputting the replaced layout as the required layout. In this method, all simulation bad points are located and the variable areas corresponding to the bad points are selected, and they are classified as a whole, and then the representative is selected from the classification and brought into the repair process for repair. After the repair is completed, other wholes of the same type are directly replaced, thereby realizing the repair of all simulation bad points, and the repair is more comprehensive while greatly reducing the time requirement for repair.

[0016] 2. In the simulated bad pixel repair method of the present invention, the variable region is a rectangular region. The shape of the variable region is limited to facilitate the region selection during the extraction process and the replacement process after the repair is completed, further reducing the time requirement for repair.

[0017] 3. The simulation bad point repair method of the present invention obtains the graphics at all the simulation bad point coordinates, and classifies the graphics based on the preset standard, including matching and classifying the graphics according to the geometric attributes of the simulation bad point, and specifically includes the following steps: obtain all the geometric graphics at the simulation bad point coordinates and classify them, and define the preset repair strategy for each type; obtain the corresponding geometric graphics type of each simulation bad point, and select the corresponding preset repair strategy. Through this method, different optimization variables are obtained according to the preset repair strategies defined for different types, and different repair processes are completed corresponding to different graphics types from the local corresponding processing, so that the repair of the simulation bad point is targeted, the results are more complete and more comprehensive, and the repair time is greatly reduced.

[0018] 4. The simulated bad pixel repair method of the present invention includes using a multivariable optimization function to repair simulated bad pixels. This method not only targets macroscopic geometric figures, but also performs more targeted repairs based on various parameters of the geometric figures, i.e., optimization variables, so that the entire repair process does not completely rely on the local geometric properties of the simulated bad pixels, thereby having greater universality, thereby achieving a more comprehensive and systematic simulated bad pixel repair method.

[0019] 5. The simulation bad point repair method of the present invention selects a classification representative from each classification, and brings it into the simulation bad point repair process of the initial layout for progressive repair, including the following steps: preliminary optimization based on the simulation bad points and corresponding optimization variable areas in the selected classification representative; judging whether the layout after the initial optimization has been repaired; if the repair is completed, exiting the repair process; if the repair is not completed, iterating the above-mentioned preliminary optimization process for the selected classification representative until the simulation bad points are completely repaired and exiting the repair process. Through this method, the selected classification representative is iteratively repaired until the repair is completed, and then other simulation bad points and corresponding variable areas of the same type are replaced, and finally the repair of all simulation bad points in the entire layout is realized. By using local optimization and progressive repair methods, on the basis of maintaining the universality of the repair strategy as much as possible, a mechanism is established to automatically and dynamically select a specific repair strategy according to the type of geometric figure of the bad point, so that the entire lithography simulation bad point repair process is more scalable.

[0020] 6. The simulation bad pixel repair method of the present invention also includes the following steps before the initial optimization based on the simulation bad pixel and the corresponding variable area in the selected classification representative: based on the selected classification representative, placing the contour line evaluation index at the coordinate of the simulation bad pixel in a preset placement mode; judging whether the contour of the figure at the coordinate of the simulation bad pixel is within the contour line evaluation index; if the contour of the figure at the coordinate of the simulation bad pixel is within the contour line evaluation index, then judging that the contour of the figure has no effect on the multivariable optimization function; if the contour of the figure at the coordinate of the simulation bad pixel is outside the contour line evaluation index, then setting a penalty term in the multivariable optimization function. The placement mechanism of the contour line evaluation index is only applicable to the location where the bad pixel occurs based on the local optimization principle, so that the bad pixel can be more effectively and directly considered during the local multivariable optimization, so as to perform targeted repairs.

[0021] 7. The present invention also provides a simulation bad point repair system to implement the simulation bad point repair method described above, including an information acquisition module: used to obtain the simulation bad point position in the initial layout after lithography simulation inspection and the variable area of ​​the preset range corresponding to the bad point, and obtain the graphics at all simulation bad point coordinates; a graphic classification and screening module: classify the graphics at the simulation bad point coordinates based on the preset standard, and select a classification representative from each classification; a layout extraction and replacement module: extract the simulation bad points and corresponding variable areas of all classification representatives, obtain the repaired classification representatives and corresponding variable areas, and replace all the simulation bad points and variable areas of the same type in the repaired layout. The simulation bad point repair system has the same beneficial effects as the simulation bad point repair method described above, which will not be repeated here.

[0022] 8. The present invention also provides a storage medium, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the simulated bad pixel repair method as described above is implemented, which has the same beneficial effects as the simulated bad pixel repair method described above and will not be elaborated herein.

Brief Description of the Drawings

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 It is a flowchart of the steps of a simulated bad pixel repair method provided by the first embodiment of the present invention.

[0025] Figure 2 It is a flowchart of step S2 in a simulated bad pixel repair method provided by the first embodiment of the present invention.

[0026] Figure 3 The process flow of step S3 in a simulated bad pixel repair method provided by the first embodiment of the present invention is Figure 1 .

[0027] Figure 4 It is a flow chart of step S31 in a simulated bad pixel repair method provided by the first embodiment of the present invention.

[0028] Figure 5 The process flow of step S3 in a simulated bad pixel repair method provided by the first embodiment of the present invention is Figure 2 .

[0029] Figure 6 This is an example diagram of a variable area of ​​a simulated bad pixel repair method provided by the first embodiment of the present invention.

[0030] Figure 7 This is an example diagram of contour line evaluation points of a simulated bad pixel repair method provided by the first embodiment of the present invention.

[0031] Figure 8 This is an example diagram of the location of bad pixels in a geometric figure in a simulated bad pixel repair method provided in the first embodiment of the present invention.

[0032] Fig. 9 It is a structural schematic diagram of a simulated bad pixel repair system provided by the second embodiment of the present invention.

[0033] Fig.10 It is a schematic diagram of the structure of a storage medium provided by the third embodiment of the present invention.

[0034] Description of the accompanying drawings:

[0035] 1. Simulation bad pixel repair system; 2. Storage medium;

[0036] 11. Information acquisition module; 12. Graphic classification and screening module; 13. Layout extraction and replacement module; 21. Memory; 22. Processor; 23. Computer program. [Specific implementation method]

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] See also Figure 1 The first embodiment of the present invention provides a simulation bad pixel repair method, comprising the following steps:

[0039] S1: providing an initial layout after optical proximity correction, performing lithography simulation inspection on the initial layout, locating the simulated bad point position and the variable area of ​​the preset range corresponding to the bad point;

[0040] S2: Obtain the graphics at the coordinates of all simulated bad points and classify the graphics based on the preset standards;

[0041] S3: Select a representative category from each category, and bring the simulated bad points and corresponding variable areas of the representative category into the repair process for progressive repair;

[0042] S4: Obtain the repaired classification representative and the corresponding variable area, replace all the same type of simulation bad points and variable areas in the repaired layout, and obtain the replaced layout;

[0043] S5: Output the replaced layout as the required layout.

[0044] It should be noted that the specific method of classifying graphics based on the preset standard is to select graphics that are exactly the same or of equal proportion as one category, so the method of selecting the category representative is to randomly select a graphic in the same category as the category representative. When the graphics are diverse, the number of categories is not limited, and the shape of the graphics shall prevail.

[0045] It can be understood that in this method, all simulated bad pixels are located and the variable areas corresponding to the bad pixels are selected as a whole and classified, and then the classification representative is selected from each classification and brought into the repair process for repair. After the repair is completed, other wholes of the same type are directly replaced, thereby achieving the repair of all simulated bad pixels. The repair is more comprehensive and the time required for repair is greatly reduced.

[0046] Furthermore, please combine Figure 2 and Figure 6 , obtain the graphics at the coordinates of all simulated bad points, and classify the graphics based on the preset standards, including matching and classifying the graphics according to the geometric properties of the simulated bad points, which specifically includes the following steps:

[0047] S21: Obtain and classify all geometric figures at the coordinates of the simulated bad points, and define a preset repair strategy for each category;

[0048] S22: Obtain the corresponding geometric figure type of each simulated bad point and select the corresponding preset repair strategy.

[0049] It should be noted that different repair strategies are formulated according to different classifications of collection graphics, so that the task of solving bad pixels can be shared by multiple more targeted methods, thereby making it more likely to solve potential bad pixels.

[0050] It can be understood that through this method, different optimization variables are obtained according to the preset repair strategies defined in different types, and different repair processes are completed corresponding to different types of graphics from the local corresponding processing, so that the repair of simulation bad points is targeted, the results are more complete and comprehensive, and at the same time the repair time is greatly reduced.

[0051] Specifically, the variable region is a rectangular region centered on the bad pixel.

[0052] It should be noted that the variable region can be a rectangle or a square.

[0053] More specifically, the variable region includes an optimized variable region surrounding the simulation bad point and a fixed variable region surrounding the optimized variable region.

[0054] It should be noted that the existing technology is to repair the bad pixel by locating the mask segment directly related to the bad pixel, fine-tuning the segment, and then iterating according to the feedback of the fine-tuning. This method is simple and practical, and all kinds of bad pixels have been directly processed. The user has a strong control over the repair process. Directly controlling the fine-tuning of the segment can produce immediate results, so that the repair range remains highly localized. However, there are two obvious problems: First, although the segment must be related to the bad pixel, other surrounding segments may be the main cause. Continuously modifying this segment may be counterproductive and cannot effectively solve the current bad pixel. If the mask error enhancement factor (MEEF) at the bad pixel is relatively large, it is necessary to make a large change to the segment to have an effect, which can easily cause MRC (minimum resolvable contrast) and unreasonable mask graphics, and even affect other locations and generate new bad pixels. Secondly, there may be many places in the layout that are exactly the same, and the existing method is to solve the problem locally based on the bad pixels themselves. The same place needs to be solved multiple times with the same strategy, which results in considerable waste. Although in actual mask repair, the number of bad pixels is unlikely to be very large because the technology is relatively mature, but if the same strategy can be used in the same place, the efficiency will be significantly improved, and the consistency of the final mask can also be better maintained.

[0055] Therefore, an optimized variable area is set around the simulated bad pixel. When the segment changes in the process of repairing the simulated bad pixel, the optimized variable area is adjusted at the same time to ensure the correlation of the geometric figures. Similarly, when the geometric figures of the optimized change area are adjusted, the geometric figures in the related fixed variable area will also be fine-tuned to ensure the correlation of the figures and the consistency of the overall figures in the mask. However, since the optimized variable area has a certain area, the direct graphic impact on the surrounding fixed variable areas will be reduced.

[0056] Specifically, under normal circumstances, the extended value of the side length of the fixed variable region corresponds to the value of the side length of the optimized variable region. In a specific embodiment of the present invention, the optimized variable region is a rectangular region with a side length of 2-3um, and the fixed variable region is extended by 2-3um at both ends based on the side length of the optimized variable region. There is no restriction on the side length or area of ​​the optimized variable region and the fixed variable region. It is subject to actual conditions and adjusted with the change of the mask size. The above values ​​only correspond to the mask size in this embodiment.

[0057] It can be understood that limiting the shape of the variable region facilitates region selection during the extraction process and the replacement process after the repair is completed, further reducing the time required for repair.

[0058] Furthermore, the simulation bad pixel repair process of the initial layout includes using a multivariable optimization function to perform simulation bad pixel repair.

[0059] It should be noted that in a specific embodiment of the present invention, the multivariables are related to the changing edges of the geometric figures at the simulated bad points. During the cutting process of the figures, or changing the position of an edge will form a variable. Similarly, cutting or changing multiple edges at the same time will form multiple variables, that is, multivariables.

[0060] It can be understood that this method not only targets macroscopic types of geometric figures, but also performs more targeted repairs based on various parameters of the geometric figures, namely, optimization variables, so that the entire repair process does not completely rely on the local geometric properties of the simulated bad points, thereby having greater universality, and thus achieving a more comprehensive and systematic simulated bad point repair method.

[0061] Further, please combine Figure 3 , Figure 4 and Figure 7 , after selecting a category representative from each category, the specific steps include:

[0062] S31: placing contour line evaluation indicators at the simulated bad point coordinates in a preset placement manner based on the selected classification representatives;

[0063] S32: judging whether the contour of the graphic at the coordinate of the simulated bad point is within the contour line evaluation index;

[0064] S32a: If the contour of the graphic at the coordinates of the simulation bad point is within the contour line evaluation index, it is determined that the contour of the graphic has no effect on the multivariable optimization function;

[0065] S32b: If the contour of the figure at the coordinates of the simulation bad point is outside the contour line evaluation index, a penalty item is set in the multivariable optimization function.

[0066] It should be noted that the selection process of simulation bad points is the deviation process of simulation bad points based on the initial contour evaluation point. When a certain edge of the figure deviates from the initial contour evaluation point, the coordinates of the edge will be defined as a simulation bad point, and a penalty item will be set for the simulation bad point, that is, a new contour evaluation index will be redefined, so as to ensure that the edge of the geometric figure that deviates from the initial contour evaluation point is adjusted to meet the redefined contour evaluation index, that is, the contour requirement with a lower level of accuracy. When the edge of the adjusted figure meets the new contour evaluation index, the simulation bad point is repaired.

[0067] Understandably, the placement mechanism of the contour evaluation index is only applicable to the location where the bad pixel occurs based on the local optimization principle, so that the bad pixel can be considered more effectively and directly during the local multivariable optimization, thereby performing targeted repairs.

[0068] Specifically, placing the contour line evaluation index at the simulated bad point coordinates in a preset placement manner based on the selected classification representative specifically includes the following steps:

[0069] S311: Based on the selected classification representative, two contour line evaluation points based on the inside and outside of the geometric figure are placed at the simulated bad point coordinates according to the specifications of the lithography simulation inspection;

[0070] S312: The gap area between two contour evaluation points constitutes a contour evaluation index.

[0071] It should be noted that the mask layout has an initial contour evaluation point, which serves as the initial evaluation standard for simulated bad pixels and is the highest standard requirement. When the edge of the mask pattern deviates from the initial contour evaluation point, it cannot meet the highest standard, and a secondary standard needs to be formulated to ensure the relevance and consistency of the entire pattern. Two inner and outer contour evaluation points are set. The inner and outer here refer to the positional relationship of the edge of the mask pattern at the bad pixel position relative to the mask pattern. One of the two contour lines is set inside the mask pattern, and the other is set outside the mask pattern. The inner and outer contour evaluation points are on the same line as the initial contour evaluation point. When the edge of the mask pattern is adjusted to be between the two contour evaluation points, the standard is met, and the relevance and consistency requirements of the entire pattern can be met after the minimum repair step.

[0072] In addition, there is no restriction on the distance between the inner and outer contour evaluation points, and it can be flexibly adjusted according to the size of different layouts. The distance between the contour evaluation points set will be different for different layout sizes.

[0073] Further, please combine Figure 5-Figure 8 , bringing the simulated bad pixels represented by the selected classification and the corresponding variable areas into the bad pixel repair process for progressive repair includes the following steps:

[0074] S33: performing preliminary optimization based on the simulation bad points in the selected classification representatives and the corresponding optimization variable regions;

[0075] S34: Determine whether the layout after initial optimization has been repaired;

[0076] S341: If the repair is completed, exit the repair process;

[0077] S342: If the repair is not completed, iterate the above-mentioned initial optimization process for the selected classification representative until the simulated bad point is completely repaired and exit the repair process.

[0078] It should be noted that the essence of lithography simulation bad dots is to locate the local area through simulation bad dots, and then carry out an optimization problem for the local area that is different from the global processing of the optical proximity correction (OPC recipe) for verification. Therefore, special treatment of bad dots in local areas is the core of the simulation bad dot repair process. In the process of repairing simulation bad dots brought into the repair process, only the classification representative is repaired, and the geometric figures corresponding to other simulation bad dots in the same category are not repaired, which reduces the repair base and the amount of calculation, thereby improving the optimization efficiency. After the optimization is completed, the same type of geometric figures, that is, other figures in the same category, are replaced to complete the repair of the corresponding simulation bad dots.

[0079] Specifically, the bad pixel repair process can be divided into three major stages.

[0080] The first stage: direct multivariable optimization, that is, marking the local areas around the bad pixels in a mask image as variables, and then solving the bad pixels through multivariable optimization. In this way, the task of solving the bad pixels is shared by multiple local areas, which can increase the possibility of solving potential bad pixels.

[0081] The second stage: repair according to the macro geometric type of the location where the bad pixel occurs, according to the specific repair strategy. That is, pre-define some repair strategies for different macro geometric types, such as Line, end, Z-Shape, or corner, and then select the corresponding repair strategy according to the geometric type of the bad pixel coordinate location.

[0082] The third stage: Continue to use the existing technology, directly fine-tune the segments related to the bad pixels, and iterate based on the feedback from the fine-tuning to repair the bad pixels. This stage can be considered as a backup for the previous steps. For the bad pixels that were not solved in the previous steps, the final effort is made in a simple and direct way.

[0083] In a specific embodiment of the present invention, in the first stage, a fixed variable region needs to be demarcated outside the optimization variable region. The segments in the fixed variable region do not participate in the optimization and maintain the state after the optical proximity correction processing is verified, but will be included in the consideration range of the middle region simulation as the surrounding environment. In addition, in conjunction with the multivariable optimization mechanism, no matter how the initial contour evaluation points of the OPC Recipe are placed before, in this embodiment, contour evaluation points (merit points) will be added at the location where the bad pixel occurs, and the inner and outer merit points will be placed according to the specifications (Spec) of the lithography simulation detection (LRC) inspection, thereby forming a contour evaluation index. That is, when the simulation contour at this location is within this contour evaluation index, the impact on the evaluation function of the local multivariable optimization is 0 (that is, no impact), but when the simulation contour exceeds this contour evaluation index, an additional penalty term will be generated in the evaluation function. This placement mechanism is only very locally applicable to the location where the bad pixel occurs, so that the bad pixel can be considered more effectively and directly during the local multivariable optimization.

[0084] For the simulated bad pixels that have not been repaired in this stage, you can enter the second stage to continue repairing them with the current repair results.

[0085] The repair strategy of the second stage includes re-adjusting the segments break settings of the mask geometry edges to obtain different optimization variables, and can also include adjusting the contour settings, etc. The optimization method can continue to use the multivariate optimization of the first stage. The biggest difference here is that according to the macroscopic geometric graphics, a special processing strategy is added. The essential logic is that the first stage adopts a local optimization algorithm, but with a more universal repair strategy. In addition to adding merit points directly at the bad pixel position, the basic optimization settings such as segments breaking and meritpoint placement are consistent with the original OPC Recipe. When this universal approach cannot solve the bad pixel, it is necessary to carry out special processing according to the specific graphics type.

[0086] Similarly, bad pixels that have not been repaired in the second stage will enter the third stage for further repair in the current repair state, and so on, thus forming a comprehensive and systematic phased progressive lithography simulation bad pixel repair mechanism as a whole.

[0087] Through this method, the selected classification representatives are repaired progressively and iteratively until the repair is completed, and then other simulated bad pixels of the same type and the corresponding variable areas are replaced, and finally the repair of all simulated bad pixels in the entire layout is achieved. Local optimization and progressive repair methods are used. On the basis of maintaining the universality of the repair strategy as much as possible, a mechanism is established to automatically and dynamically select a specific repair strategy according to the type of geometric figures of the bad pixels, making the entire lithography simulation bad pixel repair process more scalable, while enhancing the bad pixel repair capability while maintaining the locality of the repair as much as possible.

[0088] In addition, on the basis of maintaining the universality of the repair strategy as much as possible, this technical solution has established a mechanism for automatically and dynamically selecting a specific repair strategy based on the type of geometric figures of the bad pixels. Users can develop various specific strategies according to actual conditions to make the entire lithography simulation bad pixel repair process more scalable, or they can choose the simplest repair strategy possible to keep the entire process simple and universal, thereby achieving a balance suitable for the user's actual situation.

[0089] Different combinations of the steps involved in the present invention, or workflows formed by replacing one of the steps, should be considered as alternatives to this solution. For example, removing the second stage of dynamically selecting a specific repair strategy based on the type of geometric figures of the bad pixel, so that the entire process is completely independent of the local geometric properties of the bad pixel, thereby having greater universality; or replacing the second stage with a repair strategy that not only depends on the type of macroscopic geometric figures, but also specifically depends on the size of geometric parameters, so that the entire process is more targeted; or removing the third stage, so that the entire workflow depends on multivariable optimization, etc.

[0090] See also Fig. 9 The second embodiment of the present invention is to provide a simulation bad point repair system 1, which implements the simulation bad point repair method as described above, including an information acquisition module 11: used to obtain the simulation bad point position in the initial layout after lithography simulation inspection and the variable area of ​​the preset range corresponding to the bad point, and obtain the graphics at all simulation bad point coordinates; a graphic classification and screening module 12: classify the graphics at the simulation bad point coordinates based on the preset standard, and select a classification representative from each classification; a layout extraction and replacement module 13: extract the simulation bad points and corresponding variable areas of all classification representatives, obtain the repaired classification representatives and corresponding variable areas, and replace all the same type of simulation bad points and variable areas in the repaired layout. The simulation bad point repair system has the same beneficial effects as the above-mentioned simulation bad point repair method, which will not be repeated here.

[0091] See also Fig.10The third embodiment of the present invention provides a storage medium 2, including a memory 21, a processor 22, and a computer program 23 stored in the memory 21 and executable on the processor 22. When the processor 22 executes the computer program 23, the simulated bad pixel repair method as described above is implemented, which has the same beneficial effects as the simulated bad pixel repair method as described above, and will not be described in detail here.

[0092] It is understandable that, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part, and / or installed from a removable medium. When the computer program is executed by the central processing unit (CPU), the above functions defined in the method of the present application are executed. It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. Computer-readable storage media, for example, include but are not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus or a device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus or a device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0093] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0094] In the embodiments provided by the present invention, 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 determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0095] It should be understood that the "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 invention. 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 one or more embodiments in any suitable manner. Those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0096] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0097] The flow chart and block diagram in the accompanying drawings of the present invention illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which is determined based on the functions involved. It should be particularly noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs a specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0098] Compared with the prior art, the simulated bad pixel repair method, system and storage medium of the present invention have the following advantages:

[0099] 1. The simulation bad point repair method of the present invention includes the following steps: providing an initial layout after optical proximity correction, performing lithography simulation inspection on the initial layout, locating the simulation bad point position and the variable area of ​​the preset range corresponding to the bad point; obtaining the graphics at the coordinates of all simulation bad points, and classifying the graphics based on the preset standard; selecting a classification representative from each classification, bringing the simulation bad point and the corresponding variable area represented by the classification into the repair process for progressive repair; obtaining the repaired classification representative and the corresponding variable area, replacing all the simulation bad points and variable areas of the same type in the repaired layout, and obtaining the replaced layout; outputting the replaced layout as the required layout. In this method, all simulation bad points are located and the variable areas corresponding to the bad points are selected, and they are classified as a whole, and then the representative is selected from the classification and brought into the repair process for repair. After the repair is completed, other wholes of the same type are directly replaced, thereby realizing the repair of all simulation bad points, and the repair is more comprehensive while greatly reducing the time requirement for repair.

[0100] 2. In the simulated bad pixel repair method of the present invention, the variable region is a rectangular region. The shape of the variable region is limited to facilitate the region selection during the extraction process and the replacement process after the repair is completed, further reducing the time requirement for repair.

[0101] 3. The simulation bad point repair method of the present invention obtains the graphics at all the simulation bad point coordinates, and classifies the graphics based on the preset standard, including matching and classifying the graphics according to the geometric attributes of the simulation bad point, and specifically includes the following steps: obtain all the geometric graphics at the simulation bad point coordinates and classify them, and define the preset repair strategy for each type; obtain the corresponding geometric graphics type of each simulation bad point, and select the corresponding preset repair strategy. Through this method, different optimization variables are obtained according to the preset repair strategies defined for different types, and different repair processes are completed corresponding to different graphics types from the local corresponding processing, so that the repair of the simulation bad point is targeted, the results are more complete and more comprehensive, and the repair time is greatly reduced.

[0102] 4. The simulated bad pixel repair method of the present invention includes using a multivariable optimization function to repair simulated bad pixels. This method not only targets macroscopic geometric figures, but also performs more targeted repairs based on various parameters of the geometric figures, i.e., optimization variables, so that the entire repair process does not completely rely on the local geometric properties of the simulated bad pixels, thereby having greater universality, thereby achieving a more comprehensive and systematic simulated bad pixel repair method.

[0103] 5. The simulation bad point repair method of the present invention selects a classification representative from each classification, and brings it into the simulation bad point repair process of the initial layout for progressive repair, including the following steps: preliminary optimization based on the simulation bad points and corresponding optimization variable areas in the selected classification representative; judging whether the layout after the initial optimization has been repaired; if the repair is completed, exiting the repair process; if the repair is not completed, iterating the above-mentioned preliminary optimization process for the selected classification representative until the simulation bad points are completely repaired and exiting the repair process. Through this method, the selected classification representative is iteratively repaired until the repair is completed, and then other simulation bad points and corresponding variable areas of the same type are replaced, and finally the repair of all simulation bad points in the entire layout is realized. By using local optimization and progressive repair methods, on the basis of maintaining the universality of the repair strategy as much as possible, a mechanism is established to automatically and dynamically select a specific repair strategy according to the type of geometric figure of the bad point, so that the entire lithography simulation bad point repair process is more scalable.

[0104] 6. The simulation bad pixel repair method of the present invention also includes the following steps before the initial optimization based on the simulation bad pixel and the corresponding variable area in the selected classification representative: based on the selected classification representative, placing the contour line evaluation index at the coordinate of the simulation bad pixel in a preset placement mode; judging whether the contour of the figure at the coordinate of the simulation bad pixel is within the contour line evaluation index; if the contour of the figure at the coordinate of the simulation bad pixel is within the contour line evaluation index, then judging that the contour of the figure has no effect on the multivariable optimization function; if the contour of the figure at the coordinate of the simulation bad pixel is outside the contour line evaluation index, then setting a penalty term in the multivariable optimization function. The placement mechanism of the contour line evaluation index is only applicable to the location where the bad pixel occurs based on the local optimization principle, so that the bad pixel can be more effectively and directly considered during the local multivariable optimization, so as to perform targeted repairs.

[0105] 7. The present invention also provides a simulation bad point repair system to implement the simulation bad point repair method described above, including an information acquisition module: used to obtain the simulation bad point position in the initial layout after lithography simulation inspection and the variable area of ​​the preset range corresponding to the bad point, and obtain the graphics at all simulation bad point coordinates; a graphic classification and screening module: classify the graphics at the simulation bad point coordinates based on the preset standard, and select a classification representative from each classification; a layout extraction and replacement module: extract the simulation bad points and corresponding variable areas of all classification representatives, obtain the repaired classification representatives and corresponding variable areas, and replace all the simulation bad points and variable areas of the same type in the repaired layout. The simulation bad point repair system has the same beneficial effects as the simulation bad point repair method described above, which will not be repeated here.

[0106] 8. The present invention also provides a storage medium, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the simulated bad pixel repair method as described above is implemented, which has the same beneficial effects as the simulated bad pixel repair method described above and will not be elaborated herein.

[0107] The above is a detailed introduction to a simulated bad pixel repair method, system and storage medium disclosed in an embodiment of the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in the field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention. Any modifications, equivalent substitutions and improvements made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A simulation bad pixel repair method, characterized in that: The following steps are involved: Providing an initial layout after optical proximity correction, performing photolithography simulation inspection on the initial layout, locating the simulated bad point position and the variable area of ​​the preset range corresponding to the bad point; Obtain the graphics at the coordinates of all simulated bad points and classify the graphics based on the preset standards; A classification representative is selected from each classification, and contour evaluation points are placed at the coordinates of the simulated bad points of the classification representative to form a contour evaluation index. The simulated bad points of the classification representative and the corresponding variable areas are brought into the repair process for progressive repair, wherein the repair process uses a multivariable optimization function to repair the simulated bad points, and a penalty item of the multivariable optimization function is generated based on the contour evaluation index; Obtain the repaired classification representative and the corresponding variable area, replace all the same type of simulation bad points and variable areas in the repaired layout, and obtain the replaced layout; Output the replaced layout as the required layout.

2. The method for repairing a simulated bad pixel according to claim 1, wherein: The variable region is a rectangular region.

3. The method for repairing a simulated bad pixel according to claim 1, wherein: Obtain the graphics at the coordinates of all simulated bad points, and classify the graphics based on the preset standards, including matching and classifying the graphics according to the geometric properties of the simulated bad points, which specifically includes the following steps: Obtain and classify all geometric figures at the coordinates of the simulated bad points, and define the preset repair strategy for each category; Get the corresponding geometric type of each simulated bad point and select the corresponding preset repair strategy.

4. The method for repairing a simulated bad pixel according to claim 1, wherein: The variable region includes an optimized variable region surrounding a simulation bad point and a fixed variable region surrounding the optimized variable region.

5. The method for repairing a simulated bad pixel according to claim 4, wherein: Select a representative from each category and bring it into the simulation bad pixel repair process of the initial layout for progressive repair, which includes the following steps: Perform preliminary optimization based on the simulation bad points and corresponding optimization variable areas in the selected classification representatives; Determine whether the layout after initial optimization has been repaired; If the repair is completed, exit the repair process; If the repair is not completed, the above initial optimization process for the selected classification representative is iterated until the simulated bad point is completely repaired and the repair process is exited.

6. The method for repairing a simulated bad pixel according to claim 5, wherein: The following steps are also included before the initial optimization based on the simulated bad points and corresponding variable areas in the selected classification representatives: Based on the selected classification representatives, the contour line evaluation index is placed at the coordinates of the simulated bad points in a preset placement manner; Determine whether the contour of the figure at the coordinates of the simulated bad point is within the contour line evaluation index; If the contour of the figure at the coordinates of the simulation bad point is within the contour line evaluation index, it is determined that the contour of the figure has no effect on the multivariable optimization function; If the contour of the figure at the coordinates of the simulation bad point is outside the contour line evaluation index, a penalty item is set in the multivariable optimization function.

7. The method for repairing a simulated bad pixel according to claim 6, wherein: Placing the contour line evaluation index at the simulated bad point coordinates in a preset placement manner based on the selected classification representative specifically includes the following steps: Based on the selected classification representative, two contour evaluation points based on the inside and outside of the geometric figure are placed at the simulated bad point coordinates according to the specifications of the lithography simulation inspection; The gap area between two contour evaluation points constitutes a contour evaluation index.

8. A simulated bad pixel repair system, implementing the simulated bad pixel repair method according to any one of claims 1 to 7, characterized in that: It includes an information acquisition module: used to obtain the simulated bad point position in the initial layout after the lithography simulation inspection and the variable area of ​​the preset range corresponding to the bad point, and obtain the graphics at the coordinates of all simulated bad points; Graphics classification and screening module: classifies graphics at the coordinates of simulated bad points based on preset standards, and selects a representative classification from each classification; Layout extraction and replacement module: extracts simulation bad pixels and corresponding variable areas represented by all classifications, obtains the repaired classification representatives and corresponding variable areas, and replaces all simulation bad pixels and variable areas of the same type in the repaired layout.

9. A storage medium comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the simulated bad pixel repair method according to any one of claims 1 to 7 is implemented.

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