Yanbo Xu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Yanbo Xu has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Genggeng Liu
Fuzhou University
2 shared publications - Xing Huang
Northwestern Polytechnical University
2 shared publications - Yajun Xie
School of Big Data, Fuzhou University of International Studies and Trade, Fuzhou, China
1 shared publication - Youlin Pan
College of Computer and Data Science, Fuzhou University, Fuzhou 350116, China
1 shared publication - Yuhan Zhu
Fuzhou University
1 shared publication - Ziyang Chen
College of Computer and Data Science, Fuzhou University, Fuzhou 350116, China
1 shared publication
Latest Publications
- Open Access
- 21 August 2025
- Published by Springer Nature in Journal of King Saud University Computer and Information Sciences
- Vol. 37 (7) , 1-20
Multi-layer obstacle-avoiding rectilinear steiner minimal tree algorithm based on deep reinforcement learning
- 21 August 2025
- Published by Springer Nature in Journal of King Saud University Computer and Information Sciences
- Vol. 37 (7) , 1-20
Open AccessMulti-layer obstacle-avoiding rectilinear steiner minimal tree algorithm based on deep reinforcement learning
- Open Access
- 14 May 2025
- Published by MDPI AG in Micromachines
- Vol. 16 (5) , 577
SlimPort: Port-Driven High-Level Synthesis for Continuous-Flow Microfluidic Biochips
Continuous-flow microfluidic biochips (CFMBs) automatically execute various bioassays by precisely controlling the transport of fluid samples, which is driven by pressure delivered through fluidic ports. High-level synthesis, as an important stage in the design flow of CFMBs, generates binding and scheduling solutions whose quality directly affects the efficiency of the execution of bioassays. Existing high-level synthesis methods perform numerous transport tasks concurrently to increase efficiency. However, fluidic ports cannot be shared between concurrently executing transport tasks, resulting in a large number of fluidic ports introduced by existing methods. Increasing the number of fluidic ports undermines the integration, reduces the reliability, and increases the manufacturing cost. In this paper, we propose a port-driven high-level synthesis method based on integer linear programming (ILP) called SlimPort, integrating the optimization of fluidic port number into high-level synthesis, which has never been considered in prior work. Meanwhile, to ensure bioassay correctness, volume management between devices with a non-fixed input/output ratio is realized. Additionally, two acceleration strategies for ILP, scheduling constraint reduction and upper boundary estimation of fluidic port number, are proposed to improve the efficiency of SlimPort. Experimental results from multiple benchmarks demonstrate that SlimPort leads to high assay execution efficiency and a low number of fluidic ports.
- 14 May 2025
- Published by MDPI AG in Micromachines
- Vol. 16 (5) , 577
Open AccessSlimPort: Port-Driven High-Level Synthesis for Continuous-Flow Microfluidic Biochips
Continuous-flow microfluidic biochips (CFMBs) automatically execute various bioassays by precisely controlling the transport of fluid samples, which is driven by pressure delivered through fluidic ports. High-level synthesis, as an important stage in the design flow of CFMBs, generates binding and scheduling solutions whose quality directly affects the efficiency of the execution of bioassays. Existing high-level synthesis methods perform numerous transport tasks concurrently to increase efficiency. However, fluidic ports cannot be shared between concurrently executing transport tasks, resulting in a large number of fluidic ports introduced by existing methods. Increasing the number of fluidic ports undermines the integration, reduces the reliability, and increases the manufacturing cost. In this paper, we propose a port-driven high-level synthesis method based on integer linear programming (ILP) called SlimPort, integrating the optimization of fluidic port number into high-level synthesis, which has never been considered in prior work. Meanwhile, to ensure bioassay correctness, volume management between devices with a non-fixed input/output ratio is realized. Additionally, two acceleration strategies for ILP, scheduling constraint reduction and upper boundary estimation of fluidic port number, are proposed to improve the efficiency of SlimPort. Experimental results from multiple benchmarks demonstrate that SlimPort leads to high assay execution efficiency and a low number of fluidic ports.