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Its analog and mix-signal hardware implementations are proved to be applicable to high-speed image processing, video analysis, and medical signal processing with its efficiency and popularity limited by smaller implementation size and lower precision. Recently, digital implementations of CeNNs on FPGA have attracted researchers from both academia and industry due to its high flexibility and short time-to-market. However, most existing implementations are not well optimized to fully utilize the advantages of FPGA platform with unnecessary design and computational redundancy that prevents speedup. We propose a multi-level-optimization framework for energy-efficient CeNN implementations on FPGAs. In particular, the optimization framework is featured with three level optimizations: system-, module-, and design-space-level, with focus on computational redundancy and attainable performance, respectively. Experimental results show that with various configurations our framework can achieve an energy-efficiency improvement of 3.54\u00d7 and up to 3.88\u00d7 speedup compared with existing implementations with similar accuracy.<\/jats:p>","DOI":"10.1145\/3273957","type":"journal-article","created":{"date-parts":[[2018,11,29]],"date-time":"2018-11-29T13:19:30Z","timestamp":1543497570000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["A Multi-Level-Optimization Framework for FPGA-Based Cellular Neural Network Implementation"],"prefix":"10.1145","volume":"14","author":[{"given":"Zhongyang","family":"Liu","sequence":"first","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"given":"Shaoheng","family":"Luo","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1046-6379","authenticated-orcid":false,"given":"Xiaowei","family":"Xu","sequence":"additional","affiliation":[{"name":"University of Notre Dame, IN, USA"}]},{"given":"Yiyu","family":"Shi","sequence":"additional","affiliation":[{"name":"University of Notre Dame, IN, USA"}]},{"given":"Cheng","family":"Zhuo","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2018,11,28]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"1","article-title":"From layout to system: Early stage power delivery and architecture co-exploration","volume":"99","author":"Zhuo Cheng","year":"2018","journal-title":"IEEE Trans. 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