CN-121978871-A - Data processing method, electronic device, storage medium and lithographic apparatus

Abstract

Example embodiments of the present disclosure relate to a data processing method, an electronic device, a storage medium, and a lithographic apparatus. The data processing method includes sorting defect values of defect points in each block according to defect types for each block of a target layout to obtain sorted defect data of each block, wherein the defect values indicate severity of defects, grouping the sorted defect data of each block based on patterns corresponding to the defect points in each block to obtain a plurality of grouped defect data of each block, filtering the plurality of grouped defect data of each block to obtain filtered defect data of each block, and obtaining full layout defect data of the target layout based on the filtered defect data. The embodiment of the disclosure can greatly reduce the memory and the calculation time required by the full-chip defect grouping on the premise of ensuring the analysis precision.

Inventors

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Assignees

• 全芯智造技术股份有限公司

Dates

Publication Date

20260505

Application Date

20260304

Claims (16)

1. 1. A data processing method, comprising: Sequencing defect values of defect points in each block according to defect types aiming at each block of the target layout to obtain sequenced defect data of each block, wherein the defect values indicate the severity of defects; grouping the ordered defect data of each block based on a pattern corresponding to defect points within each block to obtain a plurality of grouped defect data of each block; filtering the plurality of packet defect data for each block to obtain filtered defect data for each block, and And obtaining full-layout defect data of the target layout based on the filtered defect data.
2. 2. The method of claim 1, wherein filtering the plurality of packet defect data for each block comprises: Filtering the plurality of packet defect data of each block out of the predetermined group number based on the predetermined group number to obtain the packet defect data of the predetermined group number of each block.
3. 3. The method of claim 1 or 2, wherein filtering the plurality of packet defect data for each block further comprises: the defect data in the group defect data of each block is filtered based on the predetermined reserved defect points of each group to obtain filtered defect data of each block.
4. 4. The method of claim 2, wherein the predetermined set of numbers is determined based on any one of: One or more defect types of interest selected from among all defect types; counting the top N defect types based on the historical analysis records, wherein N is a natural number, and The first K most important defect types are obtained according to a preset defect type priority rule, wherein K is a natural number.
5. 5. The method of claim 1, wherein the pattern corresponding to the defect point within each block is generated by cutting each block according to the set window size based on coordinates of each defect point.
6. 6. The method of claim 1, wherein grouping the ordered defect data for each block comprises: extracting information of a pattern within a pattern corresponding to each defective point after sorting within each block as a feature of the pattern, and Based on a predetermined matching parameter, similarity matching is performed on features of patterns corresponding to each defect point in each block after sorting to obtain a plurality of groups of patterns corresponding to a plurality of group defect data in each block.
7. 7. The method of claim 6, wherein the information of the patterns within the pattern corresponding to each defect point within each block after ordering includes one or more of a width of the patterns within the pattern, a height of the patterns within the pattern, a spacing between patterns within the pattern, and a ratio of an area of the patterns to an area of the pattern.
8. 8. The method of claim 6, wherein grouping the ordered defect data for each block further comprises: And selecting a pattern corresponding to the first defect point in each group of patterns in the multiple groups of patterns of each block as a characteristic pattern of each group of patterns, and combining the defect data of different blocks of the target layout.
9. 9. The method of claim 1, wherein the defect type comprises at least one of: Bridging risk, open circuit risk, insufficient linewidth, over-wide linewidth, pitch violations, insufficient via coverage, and antenna effect violations.
10. 10. The method of claim 1, wherein the defect data of the defect point within each block includes at least one of coordinates, a type, a defect value, and a simulation parameter.
11. 11. The method of claim 1, wherein obtaining full layout defect data for the target layout based on the filtered defect data comprises: Combining the filtered defect data of different blocks of the target layout based on the similarity of the characteristic patterns of different groups of different blocks of the target layout to obtain a plurality of combined group defect data, and And filtering the combined packet defect data to obtain filtered defect data.
12. 12. The method of claim 11, wherein filtering the merged plurality of packet defect data comprises: Filtering out packet defect data outside the predetermined group number for a plurality of packet defect data of the target layout based on the predetermined group number to obtain filtered packet defect data.
13. 13. The method of claim 11 or 12, wherein filtering the merged plurality of packet defect data further comprises: and filtering the defect data in the group defect data of the target layout based on the preset reserved defect points of each group to obtain final defect data of the target layout.
14. 14. An electronic device, comprising: processor, and A memory coupled with a processor, the memory having instructions stored therein, which when executed by the processor, cause the electronic device to perform actions comprising: Sequencing defect values of defect points in each block according to defect types aiming at each block of the target layout to obtain sequenced defect data of each block, wherein the defect values indicate the severity of defects; grouping the ordered defect data of each block based on a pattern corresponding to defect points within each block to obtain a plurality of grouped defect data of each block; filtering the plurality of packet defect data for each block to obtain filtered defect data for each block, and And obtaining full-layout defect data of the target layout based on the filtered defect data.
15. 15. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method according to any of claims 1 to 13.
16. 16. A lithographic apparatus comprising the electronic device according to claim 14.

Description

Data processing method, electronic device, storage medium and lithographic apparatus Technical Field Embodiments of the present disclosure relate to the field of chips, and more particularly, to a data processing method, an electronic device, a storage medium, and a lithographic apparatus. Background In advanced chip manufacturing, when the critical dimension (Critical Dimension, abbreviated as CD) of the circuit pattern is significantly smaller than the wavelength of the exposure light source, the actual pattern formed on the photoresist may be severely distorted with respect to the reticle design pattern due to diffraction and interference effects of light. To compensate for this optical proximity effect, optical proximity correction (Optical Proximity Correction, OPC) techniques are used to image the wafer as close as possible to the target pattern by performing inverse geometric correction (i.e., predistortion) on the mask pattern. The OPC process is typically performed by iterative simulation and verification, in each iteration, by comparing the results of the silicon imaging simulation with the target pattern, identifying a defect pattern, and adjusting OPC model parameters (flip) accordingly. However, in the early OPC debug phase, defect data on the order of hundreds of millions to billions are often generated in the full chip (full chip) range due to suboptimal parameters. In the face of such a huge amount of defect data, it is difficult for engineers to quickly locate the critical pattern and its root cause that lead to OPC failure. Disclosure of Invention According to an example embodiment of the present disclosure, a data processing method, an electronic device, a storage medium, and a lithographic apparatus are provided to at least partially solve the above or other potential technical problems. In a first aspect of the present disclosure, a data processing method is provided. The method includes sorting defect values of defect points in each block according to defect types for each block of a target layout to obtain sorted defect data of each block, wherein the defect values indicate severity of defects, grouping the sorted defect data of each block based on patterns corresponding to the defect points in each block to obtain a plurality of grouped defect data of each block, filtering the plurality of grouped defect data of each block to obtain filtered defect data of each block, and obtaining full layout defect data of the target layout based on the filtered defect data. According to the embodiment of the disclosure, the sequencing, grouping and filtering of the defect data are independently and parallelly completed in each block of the target layout, so that the memory and the calculation time required by the defect grouping of the whole layout can be greatly reduced on the premise of ensuring the analysis precision. In a second aspect of the present disclosure, an electronic device is provided. The electronic device includes a processor and a memory coupled to the processor, the memory having instructions stored therein that, when executed by the processor, cause the device to perform actions. The actions include ordering, for each block of the target layout, defect values of defect points within each block by defect type to obtain ordered defect data for each block, wherein the defect values indicate a severity of the defect, grouping the ordered defect data for each block based on a pattern corresponding to the defect points within each block to obtain a plurality of grouped defect data for each block, filtering the plurality of grouped defect data for each block to obtain filtered defect data for each block, and obtaining full layout defect data of the target layout based on the filtered defect data. In some embodiments of the present disclosure, filtering the plurality of packet defect data for each block may include filtering the plurality of packet defect data for each block except for a predetermined group number based on the predetermined group number to obtain the predetermined group number of packet defect data for each block. In some embodiments of the present disclosure, filtering the plurality of group defect data for each block may further include filtering defect data in the group defect data for each block based on the predetermined reserved defect points for each group to obtain filtered defect data for each block. In some embodiments of the present disclosure, the predetermined set of numbers may be determined based on any of one or more defect types of interest selected from among all defect types, top N defect types ranked top (e.g., most focused) based on historical analysis record statistics ranking order, where N is a natural number, and top K defect types of greatest importance derived according to preset defect type priority rules, where K is a natural number. In some embodiments of the present disclosure, a pattern corresponding to a defective point within each block