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author:

Ye, Zhengyang (Ye, Zhengyang.) [1] | Chen, Zhisheng (Chen, Zhisheng.) [2] | Pan, Youlin (Pan, Youlin.) [3] | Liu, Genggeng (Liu, Genggeng.) [4] | Guo, Wenzhong (Guo, Wenzhong.) [5] | Ho, Tsung-Yi (Ho, Tsung-Yi.) [6] | Huang, Xing (Huang, Xing.) [7]

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Abstract:

As continuous-flow microfluidic biochips technology rapidly advances, its automated synthesis methods require adapting to increasingly complex and stringent biochemical applications. In particular, with the introduction of time-sensitive bioassays, in this work, we present a timing-driven high-level synthesis method to optimize the resource efficiency of bioassays considering the time constraints. Specifically, we investigate the existing forms of time constraints and propose a corresponding flexible modeling approach based on reaction-control which can achieve downward compatibility for physical design. Additionally, we also analyze the impact of storage and wash on time constraints. The experimental results show that our method achieves efficient execution and low devices cost while satisfying time constraints. © 2024 IEEE.

Keyword:

Biochips High level synthesis Microfluidics Timing circuits

Community:

  • [ 1 ] [Ye, Zhengyang]Fuzhou University, College of Computer and Data Science, Fuzhou, China
  • [ 2 ] [Ye, Zhengyang]Engineering Research Center of Big Data Intelligence, Ministry of Education, Fuzhou, China
  • [ 3 ] [Ye, Zhengyang]Fuzhou University, Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 4 ] [Chen, Zhisheng]Xiamen University, School of Informatics, Xiamen, China
  • [ 5 ] [Pan, Youlin]Fuzhou University, College of Computer and Data Science, Fuzhou, China
  • [ 6 ] [Pan, Youlin]Engineering Research Center of Big Data Intelligence, Ministry of Education, Fuzhou, China
  • [ 7 ] [Pan, Youlin]Fuzhou University, Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 8 ] [Liu, Genggeng]Fuzhou University, College of Computer and Data Science, Fuzhou, China
  • [ 9 ] [Liu, Genggeng]Engineering Research Center of Big Data Intelligence, Ministry of Education, Fuzhou, China
  • [ 10 ] [Liu, Genggeng]Fuzhou University, Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 11 ] [Guo, Wenzhong]Fuzhou University, College of Computer and Data Science, Fuzhou, China
  • [ 12 ] [Guo, Wenzhong]Engineering Research Center of Big Data Intelligence, Ministry of Education, Fuzhou, China
  • [ 13 ] [Guo, Wenzhong]Fuzhou University, Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 14 ] [Ho, Tsung-Yi]The Chinese University of Hong Kong, Department of Computer Science and Engineering, Hong Kong
  • [ 15 ] [Huang, Xing]Northwestern Polytechnical University, School of Computer Science, Xi'an, China

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ISSN: 1948-3287

Year: 2024

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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