Reticle Enhancement Mask Modeling for Large-Design Optimization
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Solution Overview
Problem
Conventional reticle enhancement technologies face challenges in efficiently optimizing mask patterns for submicron manufacturing, particularly in handling large designs, managing computational complexity, and addressing stitching errors in tile-based computing, which affect yield and resilience to manufacturing variation.
Innovation Solution
The method involves creating a Continuous Tone Mask (CTM) and Quantized Tone Mask (QTM) for large design areas, using distributed computing to iteratively optimize tiles with updated halos, avoiding stitching issues by calculating large mask layers without stale halo data, and employing Function Sample Arrays (FSAs) for efficient memory usage and accurate pattern representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional reticle enhancement technologies are used to optimize mask patterns, then manufacturing precision can be improved, but device complexity and computational overhead increase significantly
Solution Approach 1:
The patent divides the reticle design into discrete tiles that can be processed independently and in parallel. Each tile contains pattern data and associated halo regions, allowing the computational problem to be segmented into manageable units that reduce overall computational complexity while maintaining manufacturing precision through systematic optimization of each segment.
Solution Approach 2:
The patent introduces a hierarchical processing dimension by organizing tiles into groups and processing them at multiple levels of abstraction. This dimensional approach allows simultaneous processing of multiple tiles through parallel computation while maintaining the integrity of pattern optimization across the entire reticle design.
2Productivity
If tile-based computing is used to handle large designs, then productivity can be improved through parallel processing, but stitching errors occur at tile boundaries
Solution Approach 1:
The patent applies preliminary actions by pre-processing tiles to identify and mark boundary regions before the main optimization process. Halo regions are预先 designated around each tile boundary, allowing the system to prepare for potential stitching issues before parallel processing begins, thus maintaining both productivity and stitching accuracy.
Solution Approach 2:
The patent implements feedback mechanisms where optimization results from adjacent tiles are continuously exchanged and compared at boundary regions. This feedback loop allows the system to detect and correct stitching errors by comparing halo region data from neighboring tiles, ensuring manufacturing precision is maintained while benefiting from parallel processing productivity.
3Manufacturing precision
If halo areas are updated frequently during optimization, then manufacturing precision can be maintained, but loss of time increases due to repeated computations
Solution Approach 1:
The patent employs periodic action by updating halo areas at specific intervals rather than continuously during each optimization iteration. This periodic update strategy maintains manufacturing precision by ensuring halo regions are refreshed sufficiently often while reducing computational overhead by avoiding redundant updates in every iteration, thus balancing pattern fidelity with computation time efficiency.
Data Source
AI summary
Methods for reticle enhancement technology include inputting a target wafer pattern, the target wafer pattern spanning an entire design area, and iterating a proposed mask for the entire design area until the proposed mask meets criteria towards producing the target wafer pattern. Each iteration includes calculating a predicted wafer pattern from the proposed mask. The calculating comprises calculating a cost and derivative data, the cost and the derivative data being based on comparing the predicted wafer pattern to the target wafer pattern. The cost further comprises specifications for mask manufacturability.