JP3759357B2 - Data creation method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to exposure data obtained by removing overlapping patterns from mask pattern data of a hierarchically designed semiconductor integrated circuit device, and a data creation method for creating hierarchical data for creating the exposure data.
[0002]
In the process of exposing exposure data for semiconductor integrated circuits (hereinafter simply referred to as exposure data) to a mask wafer, if there is a pattern overlap in the exposure data, multiple exposure is performed. For this reason, exposure data that eliminates pattern overlap is required. For this reason, after performing overlap removal processing on layered designed semiconductor integrated circuit mask pattern data (hereinafter simply referred to as mask pattern data), the data is subjected to format conversion processing to create exposure data. The method is taken.
[0003]
In recent years, semiconductor integrated circuits (LSIs) have been increased in scale and integration, and the amount of mask pattern data and exposure data necessary to create the LSI has also increased. Therefore, the data amount is reduced by hierarchizing the mask pattern data and the exposure data, and creating matrix-like pattern data for a repetitive pattern. However, if there is an overlap in part of the matrix pattern data, repeatability is not preserved in the above overlap removal processing, that is, the overlap must be removed by developing the matrix pattern data. Increase in data amount and conversion time to exposure data become longer. For this reason, it is required to create exposure data creation data that retains repeatability.
[0004]
[Prior art]
Conventionally, as a first method for creating exposure data, all the mask pattern data designed in a hierarchical manner is developed, and data for creating exposure data in which pattern overlap is eliminated in advance is created. Thereafter, a method has been used in which exposure data creation data that does not overlap is converted into exposure data and input to an exposure apparatus.
[0005]
Hierarchical mask pattern data has the following characteristics, and such a structure is called a hierarchical structure.
(A) The hierarchical structure is expressed in units of structures.
(B) The content of the structure includes a pattern and arrangement information of another structure.
(C) Structures having the same name are always composed of the same pattern and structure arrangement information.
[0006]
The mask pattern data has a hierarchical structure represented by the structure tree shown in FIG. 36A, and each structure and pattern is arranged as shown in FIG. The structure relationship in such a hierarchical structure is expressed in the same way as the family tree, such as a parent-child relationship.
[0007]
36A and 36B, the mask pattern data is composed of structures A, B, C, D, E, F, G and patterns P, Q, R. . In FIG. 36A, the structure is surrounded by a circle and the pattern is surrounded by a square. This notation is commonly used in the following description.
[0008]
For example, the structure B is a child structure of the structure A, and the structure D is a child structure of the structure B. Conversely, structure A is the parent structure of structure B, and structure B is the parent structure of structure D. Furthermore, structures A and B are ancestor structures of structure C, and structures D and E are descendant structures of structure A. The structure D is in a direct relationship with the structure A and in a side relationship with the structure C. In particular, the topmost structure A may be referred to as a top structure.
[0009]
Such hierarchical design is performed for the purpose of facilitating the design and reducing the amount of data as the scale of the semiconductor integrated circuit increases.
However, with the development of large scale semiconductor integrated circuits, the method for creating exposure data creation data that completely expands the mask pattern data and eliminates the overlap, the work area required during the creation process, and the created exposure data creation The amount of data becomes enormous and the creation process takes time.
[0010]
Also, in the process of converting exposure data creation data to exposure data, processing using a hierarchical structure is often performed in order to shorten the creation time and reduce the amount of data. Therefore, it is very important that the exposure data creation data has a hierarchical structure.
[0011]
Therefore, a second method of creating exposure data creation hierarchical data (hereinafter simply referred to as hierarchical data) without overlapping without performing the full development process using the hierarchical structure of the mask pattern data is conceivable.
[0012]
The second method is a method of reconstructing a hierarchy by using an overlapping pattern of mask pattern data as a pattern of the same structure, and creating hierarchical data without overlapping. For example, the mask pattern data laid out as shown in FIG. 37 has the hierarchical structure shown in FIG. The mask pattern data is composed of structures A to E, and structures C, D, and E have patterns R, S, and T, patterns P and Q, and patterns U and V, respectively (see FIG. 39).
[0013]
In this mask pattern data, the pattern S possessed by the structure C in the upper and lower tiers of the left end column overlaps the pattern Q possessed by the structure D, and the pattern S possessed by the structure C in the upper and lower tier rows overlaps the pattern U possessed by the structure E. (The overlapping part is indicated by a broken-line circle in the figure). Therefore, in the second method, the overlapping patterns Q and S and patterns S and U are developed into a common ancestor structure A. In the following, expanding a pattern to an ancestor structure will be referred to as raising the pattern to the ancestor structure.
[0014]
Incidentally, the mask pattern data has twelve structures C arranged in a matrix. Therefore, when the pattern S is lifted from a part of the structures C to the ancestor structure A, the structure C having the pattern S and the structure C not having the pattern S coexist, resulting in a contradiction. In order to avoid this, the pattern S that does not directly overlap the pattern Q or U is also lifted to the structure B (or structure A). As a result, the hierarchical data shown in FIGS. 40 is a layout diagram of hierarchical data, FIG. 41 is a hierarchical tree diagram of hierarchical data, and FIG. 42 is a layout diagram of patterns of each structure.
[0015]
In FIG. 40 to FIG. 42, the same reference numerals are given for easy understanding of the hierarchical relationship between the structure whose structure has been changed and the original structure. The lifted pattern or the OR-processed pattern is labeled so that the original pattern can be easily understood. That is, the patterns QS1 and QS2 in FIG. 41 are obtained by performing OR processing (logical sum operation) on the pattern Q and the pattern S, and the patterns SU1 and SU2 on the pattern S and the pattern U, respectively. In addition, the patterns S1 to S8 are patterns obtained by lifting the original pattern S (but not overlapping) to the structure B and developing it. The reason why the pattern S is lifted to the structure B is that the data amount is generally smaller than that when the pattern S is lifted to the structure A.
[0016]
In this way, the hierarchical structure is changed, and OR processing is performed for each structure unit (each hierarchical unit) to create hierarchical data without overlapping.
The amount of pattern data of hierarchical data created by this method is greatly reduced compared to the case of full development.
[0017]
In general, since a pattern is expressed by vertices (or line segments), the amount of pattern data is proportional to the total number of vertices of each pattern. The number of pattern vertices is compared between the data created by the second method shown in FIG. 40 and the data created by developing the first method shown in FIG. When data is created by the second method, the number of vertices is 8 in each of the patterns QS1, QS2, SV1, and SV2, and the number of vertices is 4 in each of the patterns S1 to S8, P, R, T, and V. Will be 80. On the other hand, when the data is generated by the first method, the number of vertices of the pattern is 40 for the number of vertices 4 and 4 for the number of vertices 8 (concave pattern), for a total of 192. In this way, the second method has a significant data amount reduction compared to the first method.
[0018]
[Problems to be solved by the invention]
However, even in the second method, the amount of pattern data is not sufficiently reduced depending on the data, and the amount of hierarchical data increases. In the above, since the pattern S is lifted from the structure C having the repeatable patterns R, S, and T to the structure B, the repeatability of the pattern S cannot be maintained. For this reason, for example, when the number of structures C is not 12 (= 3 × 4) but a larger number, for example, 306 (3 × 102), 302 patterns S are developed in structure B. Since the number alone is 1028 (= 4 × 302), the total number of pattern vertices is 1256. Thus, the second method also has a problem that the amount of data increases.
[0019]
In addition, since it is impossible to create data that retains repeatability, the processing efficiency of the process of converting from hierarchical data to exposure data is reduced. For example, when creating block exposure data as exposure data, there is a process of extracting a repeated pattern in a process of converting from hierarchical data to exposure data. In this extraction process, repeated patterns (patterns S2 to S7 in FIG. 42) are extracted from the lifted patterns (patterns S1 to S8 in FIG. 42). Since these patterns were originally repeatable patterns, it took twice time (development and extraction), and the processing time required for the conversion, and thus the overall processing time required to create exposure data from the mask pattern data was long. There is a problem of becoming.
[0020]
The present invention was made to solve the above problems, and its purpose is to create hierarchical data for creating exposure data while maintaining repeatability in mask pattern data designed in a hierarchical manner, It is an object of the present invention to provide a data creation method capable of reducing the data amount of the hierarchical data.
[0021]
[Means for Solving the Problems]
  In order to achieve the above object, the invention according to claim 1 is a mask pattern data having a hierarchical design.Multiple structures that make upA data generation method for generating hierarchical data for generating exposure data having no overlapping pattern from the first step of generating overlapping information between layers of overlapping patterns detected from the mask pattern data, and the overlapping Based on informationSaidOverlapping patternsPattern with lower priorityA second step of creating candidate pattern data and deletion pattern data by lifting the pattern and a third step of deleting deletion pattern data from the candidate pattern data to create non-overlapping pattern dataIn the first step, when the structures to which the overlapping patterns belong are different from each other, a higher priority is given to a pattern that is arranged in the structure and that has a larger number of the same patterns as the overlapping patterns. And setting the overlap information according to the priority.In this way, by creating pattern data that does not overlap from candidate pattern data and deletion pattern data created based on the overlap information, it is possible to create hierarchical data while maintaining almost the hierarchical structure of the mask pattern data. .
[0022]
  AlsoAs in the invention of claim 2,When the number of overlapping patterns is the same, a high priority is set for a pattern with many vertices among the overlapping patterns.
[0023]
The second step includes the step of creating the candidate pattern data and the deletion pattern data in units of layers based on the overlap information, as in the invention described in claim 3.
[0024]
In the third step, as in the invention according to claim 4, when sizing is not performed, the deletion pattern data is deleted from the candidate pattern data for each hierarchy to create hierarchical data, and when sizing, After sizing the candidate pattern data and the deletion pattern data for each layer, the deletion pattern is deleted from the candidate pattern for each layer to create hierarchical data. Thereby, correctly sized hierarchical data can be created.
[0025]
In the first step, a non-intrusion area not including the overlapping pattern is set in the first step, and a deletion pattern included in the non-intrusion area is not lifted in the second step. As a result, among the repetitive deletion patterns, the deletion pattern included in the non-intrusion area is not lifted, thereby reducing the data amount of the deletion pattern developed in the structure.
[0026]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment embodying the present invention will be described with reference to FIGS.
FIG. 2 is a block diagram schematically showing the hardware configuration of the exposure data creation apparatus of this embodiment.
[0027]
The exposure data creation device 1 includes a central processing unit (hereinafter referred to as CPU) 2 and a terminal device 3, a disk device 4, and a memory device 5 connected thereto.
The terminal device 3 includes an input device such as a keyboard and a mouse device (not shown) used for request and instruction from a user, input of parameters, etc., and a VDT, monitor, printer, etc. used for displaying pattern images, processing results, etc. Display devices.
[0028]
The disk device 4 is usually a storage device such as a magnetic disk device, an optical disk device, an optical disk device, etc., which includes program data for the exposure data creation process and first to eighth files 11 to 18 shown in FIG. The CPU 2 is activated in response to the operation of the terminal device 3, and executes exposure data creation processing according to the steps of FIG. 1 may be created in different storage devices or memory devices 5, or each file 11-18 may be created across a plurality of storage devices.
[0029]
The memory device 5 is a storage device and provides faster access than the disk device 4, but has a smaller capacity. Therefore, the CPU 2 uses the memory device 5 for the purpose of high-speed access to data with a small processing size. Note that the file 12 for storing the internal data of FIG. 1 may be created in the memory device 5.
[0030]
Program data for the exposure data creation process is provided using the recording medium 6. The recording medium 6 is a computer-readable medium such as a flexible disk, CD-ROM, hard disk, memory card, ROM, punch card, and tape.
[0031]
The recording medium 6 includes a portable storage device that can be read by a main storage device (memory device, etc.), an auxiliary storage device (disk device) of another computer that stores program data provided via a communication medium, or the computer. Includes media. Furthermore, not only a recording medium that records a program that can be directly executed by a computer, but also a recording medium that records a program that can be executed once installed on another recording medium (such as a hard disk), or an encrypted program In addition, a recording medium on which a compressed program is recorded is also included.
[0032]
The provided program data is temporarily copied or installed from the recording medium 6 to the disk device 4 and then loaded into the memory device 5 or directly loaded from the recording medium 6 to the memory device 5 and executed. In addition, even when the program is stored and provided in another computer connected via a communication medium, it is copied or installed in the disk device 4 after being received from another device via the communication medium, loaded into the memory device 5 and executed. To do.
[0033]
Next, an outline of the exposure data creation process will be described together with data stored in advance in the first to eighth files 11 to 18 or data stored in the exposure data creation process in accordance with the flowchart of FIG.
[0034]
The first file 11 stores mask pattern data as input data for exposure data creation processing. The mask pattern data is composed of pattern data of elements such as transistors, various cells, and signal wirings connecting them based on logic circuit data in advance, and the pattern data has a hierarchical structure.
[0035]
In step 21, the CPU 2 in FIG. 2 reads the mask pattern data designed in a hierarchical manner, performs OR processing for each structure (each hierarchy), and removes the overlapping pattern data in the same structure (in the same hierarchy). Arrangement data is created and stored in the second and third files 12 and 13, respectively. In step 21, the CPU 2 performs hierarchical analysis of the mask pattern data, and obtains information such as the number of patterns held by each structure, the number of arrangements of each structure, and the number of patterns when each structure is developed as a top. Ask. These pieces of information are obtained without actually fully expanding by searching the hierarchical tree of mask pattern data.
[0036]
In step 22, the CPU 2 in FIG. 2 collects pattern overlap information, and creates single lift information, joint lift information, representative information, and non-intrusion areas. Single lift information and linked lift information
(1) If the structure name of the structure to which the overlap pattern belongs is the same,
(2-A) When the structure name of the structure to which the overlap pattern belongs is different and has a direct relationship,
(2-B) If the structure name of the structure to which the overlap pattern belongs is different and is in a side relationship,
It is created according to the three cases.
[0037]
In step 23, the CPU 2 shown in FIG. 2 uses the information created in step 22 as a candidate pattern data and deletion pattern data created by performing single lifting and linking lifting of overlapping patterns, and the fourth and fifth files 14, 15. Candidate pattern data and deletion pattern data are pattern data to be subjected to graphic logic subtraction processing (SUB processing) in order to eliminate overlapping.
[0038]
Candidate pattern data is data that has been raised to an ancestor structure in order to eliminate pattern overlap, and deletion pattern data is data that has been copied to the same structure as the candidate pattern data in order to exclude overlapping portions from the candidate pattern data. Therefore, since the structure change is not added to the original pattern data designated as the deletion pattern data, the repeatability of the structure including the pattern is maintained.
[0039]
In step 24, the CPU 2 in FIG. 2 executes pattern data created by performing OR processing, sizing processing, and SUB processing on the candidate pattern data and deletion pattern data in the fourth and fifth files 14 and 15 in the sixth file. 16. By this SUB process, the part which overlaps with deletion pattern data is removed from candidate pattern data, and the pattern data without an overlap are produced.
[0040]
In step 25, the CPU 2 in FIG. 2 creates hierarchical data excluding pattern overlap by using the non-overlapping pattern data created in step 24 and the arrangement data of the third file 13. Then, the CPU 2 stores the created hierarchical data in the seventh file 17.
[0041]
In step 26, the CPU 2 in FIG. 2 converts the format of the hierarchical data created in step 25 to create exposure data, and stores the exposure data in the eighth file 18.
[0042]
A case will be described in which the processes of steps 21 to 25 are performed on the mask pattern data of FIG.
3 is a layout diagram of hierarchical data after processing, that is, without overlapping, FIG. 4 is a hierarchical tree diagram thereof, and FIG. 5 is a layout diagram of patterns of structures A, C, D, and E constituting the hierarchical data after processing. It is. The structures A to E shown in FIGS. 3 to 5 are those whose structures have been changed by the above processing. In the following description, the same reference numerals are used to make it easier to understand the correspondence before and after the creation. .
[0043]
First, in steps 22 and 23, the CPU 2 in FIG. 2 detects overlapping patterns Q and S and patterns S and U, and creates information corresponding to each of them. Then, the CPU 2 creates candidate pattern data and deletion pattern data based on the created information. In the mask pattern data shown in FIG. 37, the number of patterns Q and S and the number of patterns U and S are compared, and patterns Q and U with a small number of patterns are used as candidate patterns. The candidate pattern data 14 developed in the structure A, which is the common ancestor of each other, is created. Then, the CPU 2 creates the data 15 using the pattern S overlapping the candidate pattern data 14 as a deletion pattern. By using a pattern with a small number of arrangements as candidate pattern data, the data amount of the pattern developed in the structure is reduced.
[0044]
Next, in step 24, the CPU 2 creates data of patterns QS1, QS2, SU1, and SU2 (see FIG. 2) obtained by cutting the overlapping portion of the candidate pattern data 14 and the deletion pattern data 15 from the candidate pattern data. As a result, as shown in FIGS. 4 and 5, each structure of the created hierarchical data has structure A having patterns QS1, QS2, SU1, and SU2, structure D having pattern P, and structure E having pattern V. . The structures of the structures B and C are not changed. That is, the repeatability of the structure C (patterns R, S, T) is maintained.
[0045]
Accordingly, the total number of vertices of the pattern possessed by the hierarchical data after the above processing is 8 for the patterns QS1, QS2, SU1, and SU2, and 4 for each of the patterns P, R, S, T, and V. Therefore, it is 52 pieces. As described above, the total number of vertices was 1526 in the first conventional method, and 80 in the second conventional method.
[0046]
As described above, according to the present embodiment, the amount of hierarchical data can be significantly reduced as compared with the conventional method. Further, since the repeatability of the structure C (patterns R, S, T) is maintained, the time required for the process of converting from hierarchical data to exposure data is short, that is, the processing efficiency can be increased.
[0047]
Next, each process will be described in detail. Note that the files 11 to 18 shown in FIG. 1 and the data stored in the files necessary for describing each process will be described with reference numerals of the files storing the files.
[0048]
First, the process of step 22 will be described in detail.
FIG. 6 is a flowchart of information creation processing (information creation means) for creating simple lifting information, connection lifting information, and representative information in step 22 according to the overlapping state. That is, steps 31 to 34 in FIG. 6 are part of the sub-step of step 22. Note that FIGS. 7 to 10 are used to describe the information creation process.
[0049]
The CPU 2 sequentially selects the structures constituting the input pattern data 12 to be processed from the bottom up (in order from the bottom (lowermost layer) structure of the hierarchical tree upward), and with respect to the pattern of the selected structure. It is determined whether there is an overlap of patterns included in other structures. Then, when there is an overlap of patterns, information created for the selected structure pattern is added. When the CPU 2 loops the process for all the structure types, that is, for the structure types and determines an overlap, the CPU 2 ends the information creation process and returns to the original state.
[0050]
More specifically, step 31 is an end determination process, and the CPU 2 determines whether or not the process has been completed for all the structure types. If not, the process proceeds to step 32 to loop over all the structure types. When the process is completed for all types, the process ends and returns to the caller.
[0051]
In step 32, the CPU 2 considers the selected structure as the top structure, and investigates the overlap using the sweep method. In the overlap investigation, a frame of the child structure existing area and a pattern existing area frame are placed and the overlap is determined. When there is an overlap, the frame of the child structure existing area is replaced with the frame of the grandchild structure existing area and the frame of the pattern existing area. The CPU 2 performs this operation, finally replaces the frame of the pattern existence area with the pattern data, and detects the overlap of the patterns.
[0052]
Here, the structure existing area is a frame indicating a pattern existing area when the structure is fully developed. Hereinafter, it will be simply referred to as a frame. In addition, the frame overlap determination is made based on the identification number of the group to which the frame belongs in addition to whether there is a geometric overlap.
[0053]
By using this identification number, it is possible to prevent multiple overlaps from being investigated, and it is possible to find only the overlap of patterns that are the structures in which the closest ancestor is selected as a common ancestor.
[0054]
This identification number is given as follows. The selected structure and its child structure are all given different identification numbers. The same identification number as the parent structure is given to the frame of the selected structure and the structures other than its child structures (grandchild, great-grandchild structure, etc.). Further, the same identification number as that of the belonging structure is given to the frame of the pattern.
[0055]
For example, a procedure for finding an overlap in the pattern data shown in FIGS.
The structure of the pattern data will be described. As shown in FIG. 8, the structure A has two child structures B, the structure B has two child structures C, and the structure C has patterns P and Q.
[0056]
As shown in the lower right of FIG. 7, the two structures C included in the structure B overlap, and the pattern P included in the two structures C overlaps in the structure B. Furthermore, as shown in the upper left of FIG. 7, there is an overlap in the two structures B that the structure A has.
[0057]
The CPU 2 selects the structures in the order of structures C, B, A from the bottom up.
First, since the structure C selected first is the bottom structure, the CPU 2 does not check the overlap.
[0058]
Next, the CPU 2 checks the overlap of the selected structure B. FIGS. 9A to 9C are explanatory diagrams for examining the overlap of the structure B. FIG.
In FIG. 9A, the CPU 2 places a frame of the child structure C in the structure B, and gives different identification numbers 1 and 2 to the frame of the child structure. The given identification number is shown in parentheses in the figure. Since the frame of the structure C has an identification number different from that of the geometric overlap, it is overlapped.
[0059]
In FIG. 9B, the CPU 2 places frames of the patterns P and Q of the child structure C in the structure B, and gives the same identification numbers 1 and 2 as the belonging structure C to the frames of the patterns P and Q, respectively. Since the frame of the pattern P has an identification number different from the geometric overlap, the CPU 2 determines that “there is overlap”. On the other hand, since the frame of the pattern Q has no geometric overlap, the CPU 2 determines that “no overlap”.
[0060]
In FIG. 9C, the CPU 2 finally compares the pattern data (line segment data, etc.) of the pattern P with the frame of the pattern P determined to be “overlapping”, and “overlapping the pattern P based on the comparison result. It is determined as “Yes” and the overlap is determined.
[0061]
Next, a case where the overlap in the structure A is examined will be described. FIGS. 10A to 10D are explanatory diagrams for examining the overlap of the structure A. FIG.
In FIG. 10A, the CPU 2 places a frame of the child structure B on the structure A, and gives different identification numbers 1 and 2 to the frame of the child structure. Since the frame of the structure B has an identification number different from the geometrical overlap, the CPU 2 determines that “there is overlap”.
[0062]
In FIG. 10B, the CPU 2 places a frame of a child structure C (a grandchild structure of the structure A) in the structure A, and gives the same identification numbers 1 and 2 as the parent structure B to the frame of the structure C, respectively. All the frames of the structure C are geometrically overlapped, but the identification numbers are different only in the frame of the structure C that creates the middle overlap. Therefore, the CPU 2 determines that the frames of the two structures C in the middle are “overlapping”.
[0063]
In FIG. 10C, the CPU 2 places the frame of the pattern of the structure C that creates the middle overlap in the structure A, and gives the same identification numbers 1 and 2 as the belonging structure C to the frame of the pattern. Since the frame of the pattern P has an identification number different from the geometric overlap, the CPU 2 determines that “there is overlap”. On the other hand, since the frame of the pattern Q has no geometric overlap, the CPU 2 determines that “no overlap”.
[0064]
In FIG. 10D, the CPU 2 finally compares the pattern data (line segment data, etc.) of the pattern P using the frame of the pattern P determined to be “overlapping”, and “overlapping the pattern P based on the comparison result. It is determined as “Yes” and the overlap is determined.
[0065]
According to this method, it is possible to efficiently find the overlapping patterns P and Q that are the structures in which the closest ancestors are selected from the common ancestors without developing them.
[0066]
When determining that the patterns P and Q are overlapped as described above, the CPU 2 proceeds from step 33 to step 34 in FIG. 6 and adds information to the overlapping patterns in step 34. This addition of information is invoked each time an overlap is found in the pattern in the overlap investigation. Therefore, in the case of the data shown in FIGS. 7 and 8, the information addition in step 34 is called once in the structure B and once in the structure A.
[0067]
Next, the procedure for creating the single lifting information, the connection lifting information, the representative information, and the non-intrusion area will be described with reference to FIGS.
FIG. 11 is a flowchart showing a procedure for creating single lifting information, connection lifting information, representative information, and non-intrusion areas for two overlapping patterns. Here, two overlapping patterns are illustrated and described as patterns P and Q.
[0068]
Step 41 is a priority determination process, and the CPU 2 in FIG. 2 determines each priority according to the overlapping state of the patterns P and Q. Step 42 is information addition processing, and the CPU 2 adds information on the patterns P and Q as single lifting information and connection lifting information based on the priority determined in step 41. Step 42 includes the determination process of step 43 and the additional processes of steps 44a to 44c, 45a to 45d, and 46a to 46c based on the determination result. More specifically, based on the priority numbers of the two patterns P and Q determined in step 41, the CPU 2 performs steps 44a to 44c when the priority number of the pattern Q is large, and step 45a when the priority numbers are the same. If the priority number of the pattern P is large, steps 46a to 46c are executed.
[0069]
When these processes are completed, the CPU 2 executes an area setting process in step 47. In step 47, the CPU 2 sets a non-intrusion area using the existing areas of patterns P and Q and the sizing width. The non-intrusion area is set so as not to lift unnecessary deletion patterns.
[0070]
Next, each process will be described in detail.
First, the priority determination process in step 41 will be described.
The CPU 2 determines the priority according to the pattern overlap state, specifically, the structure to which the pattern belongs. The relationship between the overlapping situation and the priority is as follows.
(1) The structure name to which the overlapping pattern belongs is the same. Both patterns have the same priority.
(2) The structure name to which the overlapping pattern belongs is different.
(2-A) When there is a direct relationship, a pattern belonging to a structure corresponding to a descendant is set as a high priority.
(2-B) If there is a side-by-side relationship, a pattern belonging to a structure with a large number of arrangements when expanded is set to a high priority. If the number of arrangements in the case of development is the same, a pattern having a large number of pattern vertices is set as a high priority. If the number of vertices is the same, the priority is the same.
[0071]
The relationship between the priority, the connected lifting information, and the individual lifting information is as follows.
(1) When priority is the same. The joint development number of each pattern is added as joint lifting information, and the single development number of each pattern is added as single lifting information.
(2) When the priorities are different. The joint development number of each pattern is added as joint lifting information, and the single development number of a pattern with a low priority is added as single lifting information.
[0072]
Here, a single expansion number and a connected expansion number will be described.
12A, 12B, and 13 are diagrams for explaining the expansion numbers. The expansion number is an identification number that uniquely identifies the pattern in the expansion image when a certain structure is fixed. Specifically, it can be determined by the following procedure.
[0073]
(1) The number of patterns held in each structure (the number of patterns directly held) and the number of developed patterns (number of patterns in the developed image) are obtained (FIG. 12A). This number is obtained by following the hierarchical tree in the pre-processing in step 21 of FIG.
[0074]
(2) A number is assigned to the parent-child relationship of the input pattern data as shown in FIG. The general rule of assignment is that when structure X has child structures Y and Z, structure X has Nx patterns, Ny expansion patterns of structure Y, and Nz expansion patterns of structure Z. A number of 0 to Nx-1 is assigned to the possession pattern of N, Nx to Nx + Ny-1 to the possession pattern of Structure Y, and a number of Nx + Ny to Nx + Ny + Nz-1 to the possession pattern of Structure Z.
[0075]
(3) The expansion number is obtained by adding the minimum value of the assigned numbers. In FIG. 13, the numbers assigned to the structures and patterns are displayed in the vicinity thereof. When the structure A is used as a reference, the expansion number of the pattern S (pattern indicated by an arrow) that is the third from the left is (number 5 assigned to the structure B that is the second from the left) + (assigned to the structure D Number 1) + (Number 1 assigned to pattern S) = 7. Further, the development number of the third pattern S from the left when the structure B is used as a reference is (number 1 assigned to the structure D) + (number 1 assigned to the pattern S) = 2.
[0076]
The consolidated expansion number is a thing in which the link information is reflected in the expansion number. The calculation rule is calculated by selecting one representative expansion number from the expansion numbers of the connected patterns and replacing it with the expansion number selected as the representative in the ancestor structure. And the expansion number itself which does not reflect connection information becomes a single expansion number.
[0077]
14 and 15 are diagrams for explaining the difference between the single expansion number and the linked expansion. The patterns P and Q overlap, and the structure Y is assigned the number 1000, the structure Z is 200, the structure A is 100, the structure B is 20, the structure C is 10, the structure D is 35, and the structure E is 40. . In this case, the independent expansion number and the connected expansion number based on each of the structures X to E are as shown in FIG.
[0078]
The difference is in the single expansion number and the connected expansion number of the pattern Q based on the structures X, Y, and Z. This difference is that the patterns P and Q are connected by the structure A, and the ancestor structure of the structure A is replaced with the connection expansion number of P as a representative.
[0079]
Next, a method of adding a single expansion number to the single lifting information and a method of adding linked expansion to the expansion lifting information will be described.
FIG. 16 is a diagram for explaining the data structure of each piece of information.
[0080]
The single lifting information has information on a single expansion number and a representative information pointer in structure units.
The link lifting information has information of link expansion number, link pointer, and representative information pointer in structure units. The connection pointer is created according to the pattern connection.
[0081]
The representative information is information common to the connected patterns. The representative development number is a development number arbitrarily selected from the connected patterns. The lifting flag is a flag indicating whether or not a pattern having the same connected development is further lifted to an ancestor structure.
[0082]
Next, the information addition process in step 42 in FIG. 11 will be described.
FIGS. 17, 18A, and 18B are diagrams for explaining information addition of each structure.
[0083]
In the pattern data having the structure shown in FIG. 17, if the pattern P and the pattern Q are overlapping patterns, the belonging structure of the pattern P is the structure D, the belonging structure of the pattern Q is the structure F, and the common ancestor and the nearest structure is selected. Structure A.
[0084]
As shown in FIG. 18 (a), bottom-up (structures D, C, B of the structures D, C, B) is provided at the positions corresponding to the structures B, C, D between the pattern P and the structure A, as shown in FIG. Add in order).
[0085]
As shown in FIG. 18 (a), the information on the pattern Q is used as the sole lifting information, and as shown in FIG. 18 (a), bottom-up is performed at a location corresponding to the structures E and F between the pattern Q and the structure A (in the order of structures F, E, A) To add.
[0086]
The reason for adding information bottom-up is to calculate a single expansion number and a consolidated expansion number in each structure.
Further, when adding to the structure A, the flag for raising the representative information is turned off, and the others are turned on, and the information of the pattern P and the pattern Q is connected using the connection pointer.
[0087]
Next, the area setting process in step 47 of FIG. 11 will be described.
FIG. 19 is a diagram for explaining a non-intrusion area. The initial value of the non-intrusion area is set to the structure existing area, and the area side is set backward so as not to intersect with the overlapping pattern existing area. In FIG. 19, the area indicated by the solid line is the existence area of the structure including the pattern P, and the right side of the area is indicated by a one-dot chain line so as not to intersect the existence area of the overlapping patterns P and Q (area indicated by the thick broken line on the right side). Set it back to the position indicated by.
[0088]
If sizing is specified, the sizing width x2 is further retracted inward. In FIG. 19, when there is sizing designation, an area (area indicated by a thick broken line on the left side) set backward by twice the sizing width from the position indicated by the alternate long and short dash line is set.
[0089]
FIG. 19 shows a case where a non-intrusion area is set for a structure including the pattern P. Similarly, a non-intrusion area is also set for a structure including the pattern Q.
[0090]
The backward direction is selected from the four directions of up, down, right and left, and the direction in which the area area after setting is maximized is selected. The non-intrusion area is set for the structure between the selected structure A and the patterns P and Q. For example, in the pattern data having the structure of FIG. 17, the structures B, C, D, E, and F are structures between the structure A and the patterns P and Q.
[0091]
Next, the process of step 23 in FIG. 1 will be described in detail.
FIG. 20 is a flowchart showing a procedure for creating candidate pattern and deletion pattern files in step 23. That is, steps 51 to 55 in FIG. 20 are substeps of step 23.
[0092]
First, the CPU 2 in FIG. 2 loops the steps 51 and 52 by the structure type, that is, the single lifting process of the step 52 is performed for all the types of structures constituting the pattern data bottom-up by the determination process of the step 51. In step 52, the CPU 2 performs the single lifting of the pattern using the single lifting information from the input pattern data 12, and creates temporary candidate pattern data 14a.
[0093]
Next, the CPU 2 loops the steps 53 and 54 by the structure type, that is, the connection lifting process of the step 54 is executed for all types of the structures constituting the pattern data from the bottom up by the determination process of the step 53. In step 54, the CPU 2 uses the lifting information from the temporary candidate pattern data 14 a to perform pattern connection lifting and create deletion pattern data 15.
[0094]
Then, in step 55, the CPU 2 creates the candidate pattern data 14 by synthesizing the temporary candidate pattern data 14a and the deletion pattern data 15 in the case of sizing, and in the case of no sizing, the CPU 2 uses the temporary candidate pattern data 14a as the candidate pattern. 14
[0095]
21 and 22 are flowcharts showing the procedure of the single lifting in step 52 of FIG.
The structure selected from the input pattern data 12 in step 51 will be described as structure A.
[0096]
First, the CPU 2 in FIG. 2 determines whether there is an unprocessed pattern among the patterns held by the structure A in the determination process of step 61, so that the structure A directly holds the steps 61 to 63a and 63b. Loops as much as the current pattern.
[0097]
In step 62, the CPU 2 checks whether there is a single development number that matches the single lift information corresponding to the selected pattern and the structure A. If there is a match, it is determined to lift, and if there is no match, it is determined not to lift. If there is a match, the corresponding representative information candidate creation flag is turned on.
[0098]
If it is determined in step 62 that the pattern is to be lifted, the CPU 2 saves this pattern in a file as single lift pattern data 14b corresponding to the structure A in step 63a. This data is a structure in which the structure A is arranged as a child structure, and is subjected to the single lifting determination again.
[0099]
On the other hand, if it is determined in step 62 that the pattern is not lifted, the CPU 2 designates this pattern as temporary candidate pattern data 14a corresponding to the structure A in step 63b, and the single lifting process for this pattern ends.
[0100]
The data structure of the single pattern data is created in units of structures as shown in FIG. 23 (left). The pattern data pointer is a storage address of input pattern data. The arrangement information is information about the position where the pattern is arranged, and is composed of XY coordinates, rotation, and magnification.
[0101]
Next, the CPU 2 loops the steps 64 to 68a and 68b corresponding to the child structure in which the structure A is arranged by the determination process of step 64 in FIG. Further, the CPU 2 loops the steps 65 to 68a and 68b by the number of the single lift pattern of the child structure B arranged in the structure A based on the single lift pattern data 14b by the determination process of step 65. Note that the single lifting pattern of the structure B is a bottom-up process, and is already created when the structure B is selected before the structure A.
[0102]
In step 66, the CPU 2 combines the arrangement information of the structure B with the arrangement information of the single lifting pattern. In this procedure, the relative arrangement information from the structure B is converted into the relative arrangement information from the structure A.
[0103]
In step 67, the CPU 2 performs the lifting determination in the same manner as in step 62 in FIG. Based on the determination result in step 67, the CPU 2 creates temporary candidate pattern data 14a in step 68a and single lift pattern data 14b in step 68b, similarly to steps 63a and 63b in FIG.
[0104]
24 and 25 are flowcharts showing the procedure for lifting the connection in step 54 of FIG.
The structure selected from the temporary candidate pattern data 14a in step 53 will be described as structure A.
[0105]
First, the CPU 2 in FIG. 2 determines whether or not there is a temporary candidate pattern in the structure A in the temporary candidate pattern data 14a in the determination process in step 71, thereby repeating steps 71 to 73 for the temporary candidate pattern of the structure A. To do.
[0106]
In step 72, the CPU 2 determines whether or not the pattern presence area is included in the non-intrusion area of the structure A. If it is included, it is determined not to lift. If it protrudes even a little, the determination based on the connected expansion number is performed.
[0107]
The determination based on the connection expansion number checks whether there is a connection expansion that matches the connection lifting information corresponding to the pattern and the structure A. If there is no match, it is determined not to lift. If there is a match, the lift flag of the representative information is referred to. If it is on, it is determined that the lift is performed, and if it is off, it is determined that the lift is not performed.
[0108]
In step 73, if the CPU 2 determines to lift in step 72, this pattern is used as a connection lifting pattern corresponding to the structure A, and the connection lifting pattern data 14c is created. The data 14c is a structure in which the structure A is arranged as a child structure, and is subjected to the connection lifting determination again. The meaning of this operation is to lift a copy of the linked lifting pattern as a deletion pattern and cut out a pattern that overlaps the temporary candidate pattern. On the other hand, if the CPU 2 determines not to lift in step 72, the CPU 2 returns to step 71 without performing a process other than step 73.
[0109]
Next, the CPU 2 loops steps 74 to 80 for the child structure in which the structure A is arranged by the determination processing in step 74 of FIG. Further, the CPU 2 loops steps 75 to 80 with the connection lifting pattern of the child structure B in which the structure A is arranged based on the connection lifting pattern data 14 c by the determination processing in step 75. Since the structure B connection lifting pattern is a bottom-up process, it is already created when the structure B is selected before the structure A.
[0110]
In step 76, the arrangement information of the child structure B is synthesized with the arrangement information of the connected lifting pattern. In this procedure, the relative arrangement information from the child structure B is converted into the relative arrangement information from the structure A.
[0111]
In step 77, the CPU 2 makes a lifting determination in the same manner as in step 72. Based on the determination result in step 77, the CPU 2 creates the connected lifting pattern data 14c in step 78, similarly to step 73 in FIG.
[0112]
In step 79, the CPU 2 determines whether or not to create a deletion pattern based on the candidate creation flag. When this flag is on, a temporary candidate pattern of the structure A is created with a pattern linked to this pattern. Therefore, the CPU 2 creates the deletion pattern data 15 of the structure A in step 80 in order to cut out this temporary candidate pattern.
[0113]
When the deletion pattern data 15 is created as described above, the CPU 2 ends the connection lifting process and returns. That is, the CPU 2 moves to step 53 in FIG. If it is determined in step 53 that the connection lifting process has been completed for all types of structures, the CPU 2 proceeds to step 55.
[0114]
In step 55, the CPU 2 creates candidate pattern data 14 from the created temporary candidate pattern data 14 a and deletion pattern data 15. When there is no sizing, the CPU 2 uses the temporary candidate pattern data 14a as it is as the candidate pattern data 14. On the other hand, in the case of sizing, the CPU 2 synthesizes the temporary candidate pattern data 14 a and the deletion pattern data 15 in units of structures (graphic logical OR operation) to obtain candidate pattern data 14.
[0115]
In step 55, by combining the temporary candidate pattern data 14a and the deletion pattern data 15 in units of structures, it is possible to prevent the patterns from separating and generating slits during negative sizing in the sizing process.
[0116]
FIG. 26 is a diagram for explaining the data structures of the candidate pattern data 14 and the deletion pattern data 15. Each pattern data 14 and 15 has pattern vertex data in structure units.
[0117]
Next, the process of step 24 in FIG. 1 will be described in detail.
FIG. 27 is a flowchart showing a procedure for creating pattern data from candidate pattern data and deletion pattern data in step 24. That is, Steps 81 to 83 in FIG. 27 are substeps of Step 24.
[0118]
First, the CPU 2 of FIG. 2 performs an OR process and a sizing process on the candidate pattern data 14 in step 81. Next, in step 82, the CPU 2 performs OR processing and sizing processing on the deletion pattern data 15.
[0119]
Next, in step 83, the CPU 2 SUB-processes the deletion pattern from the candidate patterns subjected to the OR process and the sizing process to create the pattern data 16.
[0120]
FIG. 28 is a flowchart showing the procedure of OR processing and sizing processing in step 24 of FIG. 1, more specifically, steps 81 and 82 of FIG. That is, Steps 91 to 95 in FIG. 28 are substeps of Step 24 (Step 81 and Step 82).
[0121]
The CPU 2 in FIG. 2 makes a loop determination based on the structure type in step 91, and performs OR processing on the candidate pattern data 14 (or the deletion pattern data 15) corresponding to the structure selected in step 92. Note that this loop need not be bottom-up.
[0122]
Next, the CPU 2 determines whether or not sizing is performed in step 93, and if there is sizing designation, steps 94 and 95 are looped. The CPU 2 makes a loop determination based on the structure type in step 94, and performs sizing processing on the data after OR processing (candidate pattern data 14 or deletion pattern data 15 after OR processing) corresponding to the structure selected in step 95.
[0123]
FIG. 29 is a flowchart showing the procedure of the SUB process in step 24 of FIG. 1, specifically, step 83 of FIG. That is, steps 101 and 102 in FIG. 29 are substeps of step 24 (step 83).
[0124]
The CPU 2 in FIG. 2 makes a loop determination based on the structure type in step 101, and SUB-processes the deletion pattern from the candidate patterns corresponding to the structure selected in step 102. By this process, the overlapping pattern is cut out from the candidate pattern. Note that this loop need not be bottom-up.
[0125]
Next, the operation of the exposure data generating apparatus configured as described above will be described according to the steps in FIG.
Hereinafter, an example in which each processing of Steps 22 to 24 is applied to the data of FIG. 37 will be described.
[0126]
[Step 22]
The overlap of patterns is investigated using the sweep method in the bottom-up order (structures E, D, C, B, A). Used in the overlap investigation in structure A, finds an overlap in 4 places. These overlaps will be described as [1], [2], [3], and [4] in the order of upper left, lower left, upper right, and lower right.
[0127]
In the place [1], the pattern Q and the pattern S overlap, and the relationship between the structures D and C to which they belong is a side-by-side relationship with different structure names, so the number of arrangements when the structures D and C are expanded is compared. . Since the number of structures D arranged is 3 and the number of structures C arranged is 6, the pattern S is a high priority pattern. Therefore, the next information addition is performed on the table.
[0128]
(1) The single expansion number of the pattern Q is added to the single lifting table corresponding to the structure D between the pattern Q and the structure A in the hierarchical tree.
(2) The connection expansion number of the pattern Q is added to the connection lifting table corresponding to the structure D between the pattern Q and the structure A in the structure A and the hierarchical tree.
[0129]
(3) The link expansion number of the pattern R is added to the link lifting table corresponding to the structures B and C existing between the pattern R and the structure A in the structure A and the hierarchical tree.
[0130]
An example of adding a table of patterns Q (1) and (2) will be described below.
FIGS. 30A to 30E are single development numbers when the structures A to E are used as a reference. All single expansion numbers are described for explanation. Actually, the single development number of only the overlapping pattern is calculated without developing the mask pattern data.
[0131]
The additional information (1) and (2) is performed simultaneously for each structure.
“Creation of information corresponding to structure D”
The single expansion number 1 (see FIG. 30D) in the structure D of the pattern Q is added to the single lifting information table corresponding to the structure D.
[0132]
The link expansion number 1 in the structure D of the pattern Q is added to the link lifting information table corresponding to the structure D. Structure D is a bottom structure, and the concatenated expansion number of pattern Q is equal to the single expansion number. In the structure D, the pattern Q does not overlap. Therefore, there is no connection pointer.
[0133]
Since the representative information lifting flag does not correspond to the structure A, it is turned on. The representative development number of the representative information is selected from the connection development number of the pattern Q and the connection development number of the pattern in which the pattern Q is connected by the structure D. Since there is only the pattern Q, 1 is selected as the representative development number.
[0134]
The pointer of the single lifting information and the linked lifting information is connected to the created representative information.
FIG. 31 is a diagram illustrating a single lifting table, a linked lifting information table, and a representative information table. In each table, each information is expressed as a set such as (single development number, representative information pointer), (concatenated development number, connection pointer, representative information pointer), (representative development number, lift flag). Each information set is distinguished by a name for identifying the information.
[0135]
In FIG. 31, the additional information corresponding to the structure D of the pattern Q at the location [1] is T1 (1, D9) for the single lift information, R13 (1, none, D9) for the joint lift information, and D9 for the representative information. (1, ON).
[0136]
“Creation of information corresponding to structure A”
Pattern Q is not added to the single lifting information table.
The link expansion number 1 in the structure A of the pattern Q is added to the link lifting information table corresponding to the structure A. The connection expansion number of the pattern Q is calculated based on the representative information of the structure D. Since the pattern Q overlaps with the pattern P in the structure A, a pointer to the information of the pattern P is set.
[0137]
Since the representative information lifting flag corresponds to the structure A, it is turned OFF. The representative information number of the representative information is selected from the connection expansion number of the pattern Q and the connection expansion number of the pattern in which the pattern Q is connected by the structure A. Selected from patterns Q and P. For example, the connection expansion number of the pattern Q is used as the representative number.
[0138]
The pointer of the link lifting information is connected to the created representative information.
In FIG. 31, the additional information for the structure A of the pattern Q of [1] is the connection lifting information R1 (1, R1, D1) and the representative information D1 (1, OFF).
[0139]
The operation for the overlap in [1] is similarly performed for the overlaps in the locations [2] to [4] to create a single lift information table, a linked information lift information table, and a representative information table, respectively.
[0140]
[Step 23]
Candidate pattern data and deletion pattern data are created based on the created single lifting information table, linked information lifting information table, and representative information table.
[0141]
Each pattern data is created in a bottom-up manner by comparing the single lift information table, the single expansion number of the link information lift information table, the link expansion number and the single expansion number of the pattern data, and the link expansion number.
[0142]
FIG. 32A is a candidate pattern with sizing, and FIG. 32B is an explanatory diagram of a deletion pattern. As shown in FIG. 32 (a), in the structure A, the patterns Q and U which the structures D and E have as the candidate patterns are lifted. As shown in FIG. 32B, a copy of the pattern S (structure C) overlapping the patterns Q and U is lifted as a deletion pattern in the structure A.
[0143]
FIG. 33A is a candidate pattern without sizing, and FIG. 33B is an explanatory diagram of a deletion pattern. As shown in FIG. 33 (a), in structure A, patterns Q and U held by structures D and E as candidate patterns and a copy of pattern S (structure C) overlapping therewith are lifted. As shown in FIG. 33B, a copy of the pattern S (structure C) that overlaps the patterns Q and U is lifted as a deletion pattern in the structure A.
[0144]
[Step 24]
When no sizing designation is made, the candidate pattern (FIG. 32 (a)) and the deletion pattern (FIG. 32 (b)) corresponding to each structure are each subjected to OR processing, and thereafter each is subjected to SUB processing.
[0145]
FIGS. 34A to 34C are explanatory diagrams of OR processing and SUB processing for the structure A. FIG. The structure A candidate pattern (pattern Q, U) shown in FIG. 34A is ORed with the structure A deletion pattern (copy of pattern S) shown in FIG. Patterns QS1, QS2, SU1, and SU2 shown in c) are obtained.
[0146]
When sizing is specified, the candidate pattern (FIG. 33 (a)) and the deletion pattern (FIG. 33 (b)) corresponding to each structure are subjected to OR processing and sizing, respectively, and then subjected to SUB processing.
[0147]
FIGS. 35A to 35C are explanatory diagrams of OR processing for structure A, minus sizing as sizing, and SUB processing. Sizing processing of the structure A candidate pattern (pattern Q + S, S + U) shown in FIG. 35A and the structure A deletion pattern (copy of pattern S) shown in FIG. These are subjected to SUB processing to obtain patterns QS1, QS2, SU1, and SU2 shown in FIG.
[0148]
As described above, according to the present embodiment, the following effects can be obtained.
(1) In step 22, overlap information between layers of overlapping patterns detected from the hierarchically designed mask pattern data 11 (input pattern data 12) is created, and in step 23, overlapping patterns are lifted based on the overlap information. The candidate pattern data 14 and the deletion pattern data 15 are created. In step 24, the deletion pattern data 15 is deleted from the candidate pattern data 14 to create pattern data 16 having no overlap. As a result, by creating the pattern data 16 that does not overlap, the hierarchical data 17 can be created while maintaining the hierarchical structure of the mask pattern data 11 substantially.
[0149]
(2) In step 22, single lift information, link lift information, and representative information are created as overlap information according to the situation based on the relationship between the structure name to which each of the overlapping patterns belongs and the mutual pattern relationship. . As a result, by changing the information to be created according to the overlapping state, the number of patterns to be developed is reduced, and an increase in the amount of hierarchical data to be created can be suppressed.
[0150]
(3) When there is sizing designation, candidate pattern data 14 is created by synthesizing temporary candidate pattern data 14a and deletion pattern data 15. As a result, by applying sizing processing to the combined candidate pattern, it is possible to prevent the patterns from separating and generating slits.
[0151]
(4) In step 24, when not sizing, the deletion pattern data 15 is deleted from the candidate pattern data 14 for each layer to create the pattern data 16, and when sizing, the candidate pattern data 14 and each layer are After sizing the deletion pattern data 15, the deletion pattern data 15 is deleted from the candidate pattern data 14 for each layer to create the pattern data 16. As a result, the pattern data 16 and the hierarchical data 17 can be created without damaging the sizing figure.
[0152]
(5) In step 22, a non-intrusion area not including an overlapping pattern is set, and in step 23, a deletion pattern included in the non-intrusion area is not lifted. As a result, it is possible to reduce the data amount of the deletion pattern developed in the structure by not lifting the deletion pattern included in the non-intrusion area among the deletion patterns having repeatability.
[0153]
(6) Since the hierarchical data 17 holding the hierarchical structure can be created, the exposure data 18 with a small amount of data can be created from the hierarchical data, and the processing time required for converting the exposure data 19 can be shortened. can do.
[0154]
In addition, you may change the said embodiment into the following aspects.
In the above embodiment, the hierarchical analysis is performed in step 21 in FIG. 1, but may be configured in step 22 or 23.
[0155]
The above embodiment can be applied not only to memory types that require highly repetitive patterns, but also to data that uses a hierarchical structure. Widely applicable to mask pattern data.
[0156]
The following embodiment is summarized and the following matters regarding the configuration of the present invention are disclosed.
(A) In the data creation method according to claim 1, in the first step, the overlap information alone is used as the overlap information in accordance with a situation based on the structure name of the structure to which each of the overlap patterns belongs and the relationship between the patterns. A data creation method comprising creating lift information, linked lift information, and representative information. In this way, by changing the information to be created according to the overlapping state, the number of patterns to be developed is reduced, and an increase in the amount of hierarchical data to be created can be suppressed.
[0157]
(B) In the data generation method described in (A) above, in the first step, (1) when the structure names of the structures to which the overlapping patterns belong are the same, (2) the structures to which the overlapping patterns belong. Based on the situation of the three cases, when the structure names are different and are in a direct relationship with each other, (3) When the structure names of the structures to which the overlapping patterns belong are different and are in a side relationship with each other, A data creation method characterized by creating single lift information, linked lift information, and representative information as overlap information.
[0158]
(C) In the data creation method according to claim 1, in the second step, the candidate pattern data in which the candidate pattern is lifted is created in a structure common to the overlapping patterns, and a copy of the deletion pattern is lifted. A data creation method comprising creating the deletion pattern data.
[0159]
(D) In the data creation method according to claim 1, the second step includes a single lifting step for creating the candidate pattern data based on the overlap information, and the deletion pattern data based on the overlap information. A data creation method comprising: a connecting lifting step.
[0160]
(E) In the data creation method according to (D), the second step further includes a step of creating candidate pattern data obtained by combining the candidate pattern and the deletion pattern when sizing is specified. A data creation method characterized by By applying a sizing process to the combined candidate pattern, it is possible to prevent the patterns from separating and generating slits.
[0161]
(F) A data creation device that creates hierarchical data for creating exposure data that does not overlap patterns from hierarchically designed mask pattern data, and collects information for collecting overlapping information between the mask pattern data layers. Means, first data creation means for creating candidate pattern data and deletion pattern data by lifting overlapping patterns based on the overlap information, and pattern data without deletion by deleting deletion pattern data from the candidate pattern data And a second data creation means for creating the data.
[0162]
(G) A computer-readable recording medium that records program data for creating hierarchical data for creating exposure data that does not overlap a pattern from hierarchically designed mask pattern data, wherein the program stores the mask pattern A step of collecting overlapping information between data hierarchies, a step of creating candidate pattern data and deletion pattern data by lifting overlapping patterns based on the overlapping information, and deleting deletion pattern data from the candidate pattern data Creating a non-overlapping pattern data.
[0163]
【The invention's effect】
As described above in detail, according to the present invention, the overlap information is created according to the situation of the overlap pattern, and the hierarchical data is created from the candidate pattern data and the deletion pattern data created based on the information, thereby expanding the information. The number of patterns to be reduced is reduced, and an increase in the amount of hierarchical data to be created can be suppressed.
[0164]
Since the candidate pattern data and the deletion pattern data are created by lifting the overlapping pattern based on the created overlap information, the hierarchical data can be created while maintaining the hierarchical structure of the mask pattern data. The processing time for converting from exposure data to exposure data can be shortened.
[Brief description of the drawings]
FIG. 1 is a flowchart of exposure data creation processing according to an embodiment.
FIG. 2 is a schematic configuration diagram of a data creation device according to an embodiment.
FIG. 3 is a layout diagram of hierarchical data for creating exposure data.
FIG. 4 is a hierarchical tree diagram of exposure data creation hierarchical data.
FIG. 5 is a pattern diagram of exposure data creation hierarchical data.
FIG. 6 is a flowchart of information table creation processing.
FIG. 7 is a layout diagram for explaining an overlap investigation.
FIG. 8 is a hierarchical tree diagram of data explaining overlap investigation.
FIGS. 9A to 9C are layout diagrams showing a procedure for checking overlap. FIG.
FIGS. 10A to 10D are layout diagrams illustrating a procedure for overlapping investigation.
FIG. 11 is a flowchart of information addition processing.
FIGS. 12A and 12B are explanatory diagrams of development numbers.
FIG. 13 is a hierarchical tree diagram of data explaining expansion numbers.
FIG. 14 is a hierarchical tree diagram of data explaining single and connected expansion numbers.
FIG. 15 is an explanatory diagram of single and connected expansion numbers.
FIG. 16 is a diagram illustrating the structure of single and connected lifting information and representative information.
FIG. 17 is a hierarchical tree diagram of data explaining the addition of overlap information.
FIGS. 18A and 18B are explanatory diagrams of a table to which overlap information is added.
FIG. 19 is an explanatory diagram of a non-intrusion area.
FIG. 20 is a flowchart of candidate and deletion pattern data creation processing.
FIG. 21 is a flowchart of a single lifting process.
FIG. 22 is a flowchart of a single lifting process.
FIG. 23 is a diagram illustrating the structure of single and connected lifting pattern data.
FIG. 24 is a flowchart of a connection lifting process.
FIG. 25 is a flowchart of a connection lifting process.
FIG. 26 is an explanatory diagram of the structure of candidate and deletion pattern data.
FIG. 27 is a flowchart of pattern data creation processing.
FIG. 28 is a flowchart of SUB processing.
FIG. 29 is a flowchart of OR processing and sizing processing.
FIGS. 30A to 30E are explanatory diagrams of single development numbers.
FIG. 31 is a diagram showing the relationship between single and connected lifting information and representative information.
32A is an explanatory diagram of a candidate pattern, and FIG. 32B is an explanatory diagram of a deletion pattern.
33A is an explanatory diagram of a candidate pattern, and FIG. 33B is an explanatory diagram of a deletion pattern.
34A to 34C are pattern diagrams after graphic logic processing.
FIGS. 35A to 35C are pattern diagrams after graphic logic processing.
36A and 36B are explanatory diagrams of hierarchical design data.
FIG. 37 is a layout diagram of mask pattern data.
FIG. 38 is an explanatory diagram of mask pattern data hierarchy.
FIG. 39 is a pattern diagram of hierarchical design data.
FIG. 40 is a layout diagram of hierarchical data according to a conventional method.
FIG. 41 is a hierarchy explanatory diagram of hierarchy data by a conventional method.
FIG. 42 is a pattern diagram of hierarchical data according to a conventional method.
FIG. 43 is a pattern diagram of hierarchical data created by expansion.
[Explanation of symbols]
11 Mask pattern data
14 Candidate pattern data
15 Delete pattern data
16 pattern data
17 Hierarchical data
18 Exposure data
22 First step
23 Second Step
24 3rd step

Claims (5)

A data creation method for creating hierarchical data for creating exposure data in which a pattern does not overlap from a plurality of structures constituting hierarchically designed mask pattern data,
A first step of creating overlapping information between layers of overlapping patterns detected from the mask pattern data;
Based on the overlap information, and a second step of creating a candidate pattern data and deleting pattern data to lift the pattern low priority among the overlapping pattern is set,
Have a third step of creating a free pattern data overlapped by deleting the deletion pattern data from the candidate pattern data,
The first step includes
If the structures to which the overlapping patterns belong are different from each other, setting a higher priority for a pattern that is arranged in the structure and that has a larger number of the same patterns as the overlapping patterns;
Creating the overlap information according to the priority;
A data creation method characterized by comprising : The data creation method according to claim 1,
A data creation method characterized in that, when the number of overlapping patterns is the same, a high priority is set for a pattern having many vertices among the overlapping patterns . The data creation method according to claim 1,
The second step includes
A data creation method comprising the step of creating the candidate pattern data and the deletion pattern data for each hierarchical unit based on the overlap information. The data creation method according to claim 1,
In the third step,
If not sizing, delete the deletion pattern data from the candidate pattern data for each hierarchy, create the hierarchy data,
In the case of sizing, a data creation method comprising: sizing candidate pattern data and deletion pattern data for each layer, and then deleting the deletion pattern from the candidate pattern for each layer to create layer data. The data creation method according to claim 1,
In the first step, a non-intrusive area not including the overlapping pattern is set,
In the second step, the deletion pattern included in the non-intrusion area is not lifted.

Images