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Podcast EP354: How Siemens EDA is Conquering New Lithography Challenges with Sagar Saxena, Sonic AI
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Podcast EP354: How Siemens EDA is Conquering New Lithography Challenges with Sagar Saxena
Semiconductor Insiders
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Jul 10, 2026
•
16:00
Interview
Podcast EP354: How Siemens EDA is Conquering New Lithography Challenges with Sagar Saxena
From
Semiconductor Insiders
Daniel Nenny
(Host, Semiconductor Insiders)
•
Sagar Tekzina
(Guest)
•
Sagar Saxena
(Senior Product Engineer, Siemens EDA)
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Executive Summary
The semiconductor industry is shifting from traditional 'Manhattan' (right-angled) mask designs to 'curvilinear' (curved) designs to improve pattern fidelity and yield at advanced nodes.
This shift creates significant computational challenges for traditional Optical Proximity Correction (OPC) methods, leading to data volume explosion and performance bottlenecks.
Siemens EDA has developed a novel 'vector-based decoupled site and anchor point framework' for OPC that separates optimization locations from correction control points.
This new framework reduces computational overhead, simplifies recipes, and enables the practical, at-scale production of curvilinear masks, which is now being adopted by leading-edge logic and memory foundries.
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The Industry Shift to Curvilinear Masks
Computational Challenges of Curvilinear OPC
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Processed Jul 10, 2026
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