VLSI layout hotspot detection based on discriminative feature extraction
Invited conference paper presented and published in conference proceedings

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其它資訊
摘要Feature extraction is a key stage in machine learning based VLSI layout hotspot detection flow. Conventional machine learning based methods apply various feature extraction techniques to approximate an original layout structure at nanometer level. However, some important layout pattern information is missed during the approximation process, resulting in performance degradation. In this paper, we present a comprehensive study on layout feature extraction and propose a new method that can preserve discriminative layout pattern information to improve the detection performance in terms of accuracy and extra. Experiments were conducted on an industrial benchmark and ICCAD benchmark suite to study the effectiveness of our proposed methods.
著者Hang Zhang, Haoyu Yang, Bei Yu, Evangeline F. Y. Young
會議名稱IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)
會議開始日25.10.2016
會議完結日28.10.2016
會議地點Jeju
會議國家/地區韓國
會議論文集題名Circuits and Systems (APCCAS), 2016 IEEE Asia Pacific Conference on
出版年份2017
月份1
日期5
出版社IEEE
頁次542 - 545
語言美式英語

上次更新時間 2020-25-10 於 02:11