4 April 2017 A random generation approach to pattern library creation for full chip lithographic simulation
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Abstract
As technology advances, the need for running lithographic (litho) checking for early detection of hotspots before tapeout has become essential. This process is important at all levels—from designing standard cells and small blocks to large intellectual property (IP) and full chip layouts. Litho simulation provides high accuracy for detecting printability issues due to problematic geometries, but it has the disadvantage of slow performance on large designs and blocks [1]. Foundries have found a good compromise solution for running litho simulation on full chips by filtering out potential candidate hotspot patterns using pattern matching (PM), and then performing simulation on the matched locations. The challenge has always been how to easily create a PM library of candidate patterns that provides both comprehensive coverage for litho problems and fast runtime performance. This paper presents a new strategy for generating candidate real design patterns through a random generation approach using a layout schema generator (LSG) utility. The output patterns from the LSG are simulated, and then classified by a scoring mechanism that categorizes patterns according to the severity of the hotspots, probability of their presence in the design, and the likelihood of the pattern causing a hotspot. The scoring output helps to filter out the yield problematic patterns that should be removed from any standard cell design, and also to define potential problematic patterns that must be simulated within a bigger context to decide whether or not they represent an actual hotspot. This flow is demonstrated on SMIC 14nm technology, creating a candidate hotspot pattern library that can be used in full chip simulation with very high coverage and robust performance.
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Elain Zou, Elain Zou, Sid Hong, Sid Hong, Limei Liu, Limei Liu, Lucas Huang, Lucas Huang, Legender Yang, Legender Yang, Aliaa Kabeel, Aliaa Kabeel, Kareem Madkour, Kareem Madkour, Wael ElManhawy, Wael ElManhawy, Joe Kwan, Joe Kwan, Chunshan Du, Chunshan Du, Xinyi Hu, Xinyi Hu, Qijian Wan, Qijian Wan, Recoo Zhang, Recoo Zhang, } "A random generation approach to pattern library creation for full chip lithographic simulation", Proc. SPIE 10148, Design-Process-Technology Co-optimization for Manufacturability XI, 1014811 (4 April 2017); doi: 10.1117/12.2258133; https://doi.org/10.1117/12.2258133
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