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An efficient and fast polarity optimization approach for mixed polarity Reed-Muller logic circuits

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Abstract

Although the genetic algorithm has been widely used in the polarity optimization of mixed polarity Reed-Muller (MPRM) logic circuits, few studies have taken into account the polarity conversion sequence. In order to improve the efficiency of polarity optimization of MPRM logic circuits, we propose an efficient and fast polarity optimization approach (FPOA) considering the polarity conversion sequence. The main idea behind the FPOA is that, firstly, the best polarity conversion sequence of the polarity set waiting for evaluation is obtained by using the proposed hybrid genetic algorithm (HGA); secondly, each of polarity in the polarity set is converted according to the best polarity conversion sequence obtained by HGA. Our proposed FPOA is implemented in C and a comparative analysis has been presented for MCNC benchmark circuits. The experimental results show that for the circuits with more variables, the FPOA is highly effective in improving the efficiency of polarity optimization of MPRM logic circuits compared with the traditional polarity optimization approach which neglects the polarity conversion sequence and the improved polarity optimization approach with heuristic technique.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 60973106, 61370059, 61232009 and 81571142), Beijing Natural Science Foundation (4152030), the National High Technology Research and Development Program (863 Project) of China (2011AA010404), Fundamental Research Funds for the Central Universities (YWF-15-GJSYS-085, YWF-14-JSJXY-14), Open Project Program of National Engineering Research Center for Science & Technology Resources Sharing Service (Beihang University), the fund of the State Key Laboratory of Computer Architecture (CARCH201507), and the fund of the State Key Laboratory of Software Development Environment (SKLSDE- 2014ZX-19).

Author information

Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, 100191, China

    Zhenxue He, Limin Xiao, Zhisheng Huo & Li Ruan

  2. School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Zhenxue He, Limin Xiao, Fei Gu, Shubin Su, Zhisheng Huo & Li Ruan

  3. School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China

    Tongsheng Xia, Rong Zhang & Xiang Wang

  4. State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China

    Longbing Zhang

  5. National Engineering Research Center for Science & Technology Resources Sharing Service, Beijing, 100191, China

    Shubin Su

Authors
  1. Zhenxue He
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  2. Limin Xiao
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  3. Fei Gu
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  4. Tongsheng Xia
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  5. Shubin Su
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  6. Zhisheng Huo
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  7. Rong Zhang
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  8. Longbing Zhang
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  9. Li Ruan
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  10. Xiang Wang
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Corresponding authors

Correspondence to Limin Xiao or Xiang Wang.

Additional information

Zhenxue He is a PhD candidate in the School of Computer Science and Engineering, Beihang University, China. His research interests include low power integrated circuit design and optimization, multiple-valued logic circuits, and computer aided design. He is amember of ACM and China Computer Federation.

Limin Xiao is a professor of the School of Computer Science and Engineering, Beihang University, China. He is a senior membership of China Computer Federation. His main research areas are computer architecture, computer system software, high performance computing, virtualization and cloud computing.

Fei Gu is a PhD candidate in the School of Computer Science and Technology, Beihang University, China. He received the MS degree of computer science and technology from Nanjing University of Aeronautics and Astronautics, China in 2014 and the BS degree of software engineering from Yangzhou University, China in 2011. His research focuses on sensor network, healthcare system, and data mining.

Tongsheng Xia is an associate professor of the School of Electronic and Information Engineering, Beihang University, China. He received his PhD in microelectronics from University of Texas at Austin, USA in 2005. His research focuses on analog CMOS integrated circuit design and next generation storage device. He has published many top papers in international journals.

Shubin Su is a PhD candidate in the School of Computer Science and Technology, Beihang University, China. He received his MS degree of computer technology from Jiangxi University of Science and Technology, China in 2014. His research focuses on computer architecture, cloud computing, and data mining.

Zhisheng Huo is a PhD candidate in the School of Computer Science and Technology, Beihang University, China. He received his MS degree from College of Computer Science, Shenyang Aerospace University, China in 2012. His research focuses on big data storage and distributed storage system.

Rong Zhang is pursuing the master degree at the School of Electronics and Information Engineering, Beihang University, China. She received her BS of electronic information engineering from Shijiazhuang Railway University, China in 2013. Her research focuses on low power integrated circuit design and optimization.

Longbing Zhang is an associate professor of Institute of Computing Technology, Chinese Academy of Sciences, China. He is an associate director of Research Center for Microprocessor. He received his PhD in computer architecture from University of Science and Technology of China, China in 2002. His research focuses on microprocessor design and parallel processing.

Li Ruan is a lecturer of the School of Computer Science and Engineering, Beihang University, China. She is a senior membership of China Computer Federation. Her main research areas are virtualization and cloud computing, computer system software, and high performance computer.

Xiang Wang is a professor of the School of Electronic and Information Engineering, Beihang University, China. He is a senior membership of Chinese Institute of Electronics and Chinese Society of Micronano Technology. His main research areas are very large scale integration, micro-nano system, genetic circuits and aerospace information networks.

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He, Z., Xiao, L., Gu, F. et al. An efficient and fast polarity optimization approach for mixed polarity Reed-Muller logic circuits. Front. Comput. Sci. 11, 728–742 (2017). https://doi.org/10.1007/s11704-016-5259-2

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  • DOI: https://doi.org/10.1007/s11704-016-5259-2

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