Mask Optimization With Minimal Number of Convolutions Using Intensity Difference Map

• Item type: Symposium(1)
• 公開日: 2014-08-21
• タイトル: Mask Optimization With Minimal Number of Convolutions Using Intensity Difference Map
• タイトル / 言語: en
• タイトル: Mask Optimization With Minimal Number of Convolutions Using Intensity Difference Map
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 物理設計
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: 東京工業大学大学院理工学研究科
• 著者所属: 東京工業大学大学院理工学研究科
• 著者所属: 株式会社東芝
• 著者所属: 株式会社東芝
• 著者所属(英): en
• 著者所属(英): Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Toshiba Corporation
• 著者所属(英): en
• 著者所属(英): Toshiba Corporation
• 著者名: Ahmed, Awad; Atsushi, Takahashi; Satoshi, Tanaka; Chikaaki, Kodama
• 著者名(英): Ahmed, Awad; Atsushi, Takahashi; Satoshi, Tanaka; Chikaaki, Kodama
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: With the continuous shrinking of minimum feature sizes beyond 193nm wavelength in optical lithography, more and more computationally expensive algorithms are being developed in the field of Optical Proximity Correction (OPC) to improve pattern fidelity and robustness against process variations. Lithography simulation time and image accuracy are proportional to the number of kernels by which the mask is convoluted to generate the intensity map for each OPC iteration. Typically, there is a trade-off between the accuracy of intensity map and computational time which can be minimized by using only one kernel. Nevertheless, the intensity of each pixel tends to be smaller than its actual value and is not accurate enough resulting in intensity error. However, with considering relaxed Edge Placement Error (EPE) conditions, we observed that the error of pixel intensity is not changed much even if the mask is slightly updated. Therefore, in this paper, we exploit this observation to relax the intensity error by constructing intensity difference map in which the differences between one kernel and multiple kernels intensity maps are stored. For each OPC iteration, one kernel is used to generate intensity map, to which the intensity difference map is added to improve its accuracy. Our experimental results show that the proposed algorithm generates mask solutions within a short computational time with almost the same EPE and process variability band obtained using multiple kernels during optimization.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: With the continuous shrinking of minimum feature sizes beyond 193nm wavelength in optical lithography, more and more computationally expensive algorithms are being developed in the field of Optical Proximity Correction (OPC) to improve pattern fidelity and robustness against process variations. Lithography simulation time and image accuracy are proportional to the number of kernels by which the mask is convoluted to generate the intensity map for each OPC iteration. Typically, there is a trade-off between the accuracy of intensity map and computational time which can be minimized by using only one kernel. Nevertheless, the intensity of each pixel tends to be smaller than its actual value and is not accurate enough resulting in intensity error. However, with considering relaxed Edge Placement Error (EPE) conditions, we observed that the error of pixel intensity is not changed much even if the mask is slightly updated. Therefore, in this paper, we exploit this observation to relax the intensity error by constructing intensity difference map in which the differences between one kernel and multiple kernels intensity maps are stored. For each OPC iteration, one kernel is used to generate intensity map, to which the intensity difference map is added to improve its accuracy. Our experimental results show that the proposed algorithm generates mask solutions within a short computational time with almost the same EPE and process variability band obtained using multiple kernels during optimization.
• 書誌情報: DAシンポジウム2014論文集; 巻 2014, p. 145-150, 発行日 2014-08-21
• 出版者 / 言語: ja
• 出版者: 情報処理学会