Paper
20 March 2018 Leveraging pattern matching to solve SRAM verification challenges at advanced nodes
Huan Kan, Lucas Huang, Legender Yang, Elaine Zou, Qijian Wan, Chunshan Du, Xinyi Hu, Zhengfang Liu, Yu Zhu, Recoo Zhang, Elven Huang, Jonathan Muirhead
Author Affiliations +
Abstract
Memory is a critical component in today's system-on-chip (SoC) designs. Static random-access memory (SRAM) blocks are assembled by combining intellectual property (IP) blocks that come from SRAM libraries developed and certified by the foundries for both functionality and a specific process node. Customers place these SRAM IP in their designs, adjusting as necessary to achieve DRC-clean results. However, any changes a customer makes to these SRAM IP during implementation, whether intentionally or in error, can impact yield and functionality. Physical verification of SRAM has always been a challenge, because these blocks usually contain smaller feature sizes and spacing constraints compared to traditional logic or other layout structures. At advanced nodes, critical dimension becomes smaller and smaller, until there is almost no opportunity to use optical proximity correction (OPC) and lithography to adjust the manufacturing process to mitigate the effects of any changes. The smaller process geometries, reduced supply voltages, increasing process variation, and manufacturing uncertainty mean accurate SRAM physical verification results are not only reaching new levels of difficulty, but also new levels of criticality for design success. In this paper, we explore the use of pattern matching to create an SRAM verification flow that provides both accurate, comprehensive coverage of the required checks and visual output to enable faster, more accurate error debugging. Our results indicate that pattern matching can enable foundries to improve SRAM manufacturing yield, while allowing designers to benefit from SRAM verification kits that can shorten the time to market.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huan Kan, Lucas Huang, Legender Yang, Elaine Zou, Qijian Wan, Chunshan Du, Xinyi Hu, Zhengfang Liu, Yu Zhu, Recoo Zhang, Elven Huang, and Jonathan Muirhead "Leveraging pattern matching to solve SRAM verification challenges at advanced nodes", Proc. SPIE 10588, Design-Process-Technology Co-optimization for Manufacturability XII, 105880Z (20 March 2018); https://doi.org/10.1117/12.2297340
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KEYWORDS
Visualization

Multilayers

Manufacturing

Intellectual property

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