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author:

Liu, G. (Liu, G..) [1] (Scholars:刘耿耿) | Xu, W. (Xu, W..) [2] | Zhou, R. (Zhou, R..) [3] | Xu, N. (Xu, N..) [4]

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Abstract:

Time-Division Multiplexing (TDM) technology is widely applied to solving the IO limitation problem to improve the routability of FPGA system. However, the increase of the TDM ratio leads to a significant increase in system delay. Therefore, a Multi-Stage Co-Optimization FPGA routing (MSCOFRouting) for Time-Division Multiplexing is proposed in this paper to optimize the system delay and the routability of FPGA system. First, an adaptive routing algorithm is proposed to reduce routing congestion, improve the routability, solve the routing optimization problem between FPGAs, and provide high-quality routing results for subsequent TDM ratio assignment. Second, to avoid the delay degradation caused by excessive TDM ratio of large-scale net groups, a TDM ratio assignment algorithm based on Lagrangian relaxation is utilized to assign the initial TDM ratio with a smaller delay to the edge distribution system of the routing graph. In addition, a multi-level TDM ratio optimization algorithm is used to reduce the TDM ratios of the net group with maximum TDM ratios. The TDM ratio reduction is employed for the net group and the FPGA connection pair. Meanwhile, a multi-thread parallelization method is integrated into the three algorithms above to improve further the efficiency of MSCOFRouter. Experiments show that MSCOFRouting can obtain the results satisfying the TDM ratio constraint, and achieve the best routing optimization results and TDM ratio assignment results. © 2023 Science Press. All rights reserved.

Keyword:

FPGA systems Lagrangian relaxation Logic verification Routing Time-division multiplexing

Community:

  • [ 1 ] [Liu G.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Liu G.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University), Fuzhou, 350116, China
  • [ 3 ] [Xu W.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Zhou R.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350116, China
  • [ 5 ] [Xu N.]School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, China

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电子与信息学报

ISSN: 1009-5896

CN: 11-4494/TN

Year: 2023

Issue: 9

Volume: 45

Page: 3430-3438

0 . 5

JCR@2023

0 . 5 0 0

JCR@2023

JCR Journal Grade:4

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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