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DTSTAMP:20240626T180002Z
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UID:dac_DAC 2024_sess145@linklings.com
SUMMARY:Unveiling Precision: Mastering the Art of Mask Manufacturing and H
 otspot Detection
DESCRIPTION:Research Manuscript\n\nJoin us at the forefront of semiconduct
 or manufacturing. Delve into how language modeling techniques can be used 
 for hotspot detection in chip layouts via semantic encoding. Discover stra
 tegies for co-optimizing source and masks in an efficient manner. Learn ab
 out the integration of correlation-aware strategies and reinforcement lear
 ning to enhance mask optimization. Explore advancements in inverse lithogr
 aphy technology (ILT) that account for mask writing realities, and appreci
 ate elegant methods for accelerating ILT computations, promising reduction
 s in turnaround time without sacrificing pattern fidelity. \nThis session 
 is a deep dive into the latest methodologies and technologies in photomask
  design, optimization, and manufacturing.\n\nCAMO: Correlation-Aware Mask 
 Optimization with Modulated Reinforcement Learning\n\nOptical proximity co
 rrection (OPC) is a vital step to ensure printability in modern VLSI manuf
 acturing. Various OPC approaches have been proposed, which are typically d
 ata-driven and hardly involve particular considerations of the OPC problem
 , leading to potential performance bottlenecks. In this pa...\n\n\nXiaoxia
 o Liang (The Hong Kong University of Science and Technology (Guangzhou)), 
 Haoyu Yang (NVIDIA), Kang Liu (Huazhong University of Science and Technolo
 gy), Bei Yu (The Chinese University of Hong Kong), and Yuzhe Ma (The Hong 
 Kong University of Science and Technology (Guangzhou))\n------------------
 ---\nEfficient Bilevel Source Mask Optimization\n\nResolution Enhancement 
 Techniques (RETs) are critical to meet the demands of advanced technology 
 nodes. Among RETs, Source Mask Optimization (SMO) is pivotal, concurrently
  optimizing both the source and the mask to expand the process window. Tra
 ditional SMO methods, however, are limited by sequentia...\n\n\nGuojin Che
 n (The Chinese University of Hong Kong), Hongquan He (Shanghai Tech Univer
 sity), Peng Xu (The Chinese University of Hong Kong), Hao Geng (Shanghai T
 ech University), and Bei Yu (The Chinese University of Hong Kong)\n-------
 --------------\nEMOGen: Enhancing Mask Optimization via Pattern Generation
 \n\nLayout pattern generation via deep generative models is a promising me
 thodology for building practical large-scale pattern libraries. \nHowever,
  although improving optical proximity correction (OPC) is a major target o
 f existing pattern generation methods, they are not explicitly trained for
  OPC and ...\n\n\nSu Zheng (The Chinese University of Hong Kong), Yuzhe Ma
  (The Hong Kong University of Science and Technology (Guangzhou)), and Bei
  Yu and Martin Wong (The Chinese University of Hong Kong)\n---------------
 ------\nEfficient ILT via Multigrid-Schwartz Method\n\nInverse lithography
  technology (ILT) is one of most powerful resolution enhancement technolog
 ies (RETs) used in chip manufacturing. Due to the high computational requi
 rements of ILT, large layouts are often split into smaller tiles and then 
 assembled to obtain the final result. This paper states the...\n\n\nShuyua
 n Sun and Fan Yang (Fudan University); Bei Yu (The Chinese University of H
 ong Kong); and Li Shang, Dian Zhou, and Xuan Zeng (Fudan University)\n----
 -----------------\nLLM-HD: Layout Language Model for Hotspot Detection wit
 h GDS Semantic Encoding*\n\nWith the rapid downscaling of technology nodes
 , \nindustrial flow such as pitch reduction, patterning flexibility, and l
 ithography processing variability have been challenged. \nLayout hotspot d
 etection is one of the most challenging and critical steps, which requires
  technology upgrading.\nPattern mat...\n\n\nyuyang chen, Yiwen Wu, Jingya 
 Wang, Tao Wu, Xumin He, Jingyi Yu, and Hao Geng (Shanghai Tech University)
 \n---------------------\nFracturing-aware Curvilinear ILT via Circular E-b
 eam Mask Writer\n\nInverse lithography technology (ILT) is vital in optica
 l proximity correction, tending to generate curvilinear masks for optimal 
 process windows. Traditional curvilinear mask manufacturing involves fract
 uring into rectangles, requiring expensive mask write times. A novel E-bea
 m mask writer that writ...\n\n\nXinyun Zhang, Su Zheng, Guojin Chen, and B
 inwu Zhu (The Chinese University of Hong Kong); Hong Xu (City University o
 f Hong Kong); and Bei Yu (The Chinese University of Hong Kong)\n\nTopic: D
 esign\n\nKeyword: Design for Manufacturability and Reliability\n\nSession 
 Chairs: Shao-Yun Fang (National Taiwan University of Science and Technolog
 y) and Biying Xu (The Hong Kong University of Science and Technology (Guan
 gzhou))
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