Presentation + Paper
23 March 2020 Dynamic pattern matching flow to enable low escape rate weak point detection
Author Affiliations +
Abstract
With multi patterning being the method of choice for pushing technology further down the shrink roadmap, new design weak points are emerging that have multi-layer components and are difficult to find and to define. On the other hand, advanced OPC methodologies like retargeting and recentering help alleviate many of the occurrences, leaving only a few locations that are critical and need to be dealt with in design. State of the art in-design weak point auto fixing is usually done by identifying a weak point by a pattern match, and providing the router either a “safe” alternative configuration or tell it to reroute locally, also called rip-and-reroute. The dilemma for developing pattern matching decks that are used in place and route tools is that one cannot be too specific in the pattern definition as there will be escapes that can possibly cause problems in the fab. Having a more general pattern definition will prevent escapes, but will flag many locations that don’t really require fixing. As a consequence, this more general pattern definition may bog down the place and route tool and can actually result in area bloat if too many rip-and-reroute areas are identified. We have come up with a patented flow that allows very specific weak point detection with a low escape rate. The flow starts with a generic pattern definition of the fail mode, but reduces the number of occurrences by identifying safe configurations. Usually, the pattern extent of the safe configuration is larger than the initial generic pattern, and may contain more layers. Any known safe configuration is added to a “good pattern” database which is then subtracted from the initial pattern match. Thus, the number of design locations that need to be auto fixed is kept at a minimum. As the technology matures, more safe patterns are found and added to the database, thus reducing the amount of auto fixing required.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Uwe Paul Schroeder, Janam Bakshi, Ahmed Mounir Elsemary, and Fadi Batarseh "Dynamic pattern matching flow to enable low escape rate weak point detection", Proc. SPIE 11328, Design-Process-Technology Co-optimization for Manufacturability XIV, 113280D (23 March 2020); https://doi.org/10.1117/12.2551739
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KEYWORDS
Databases

Image classification

Lithography

Metals

Printing

Digital electronics

Machine learning

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