Clustering- and probability-based approach for time-multiplexed FPGA partitioning

Chia-Tso Chao*, Guang Ming Wu, Iris Hui Ru Jiang, Yao Wen Chang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

17 Scopus citations


Improving logic density by time-sharing, time-multiplexed FPGAs (TMFPGAs) have become an important research topic for reconfigurable computing. Due to the precedence and capacity constraints in TMFPGAs, the clustering and partitioning problems for TMFPGAs are different from the traditional ones. In this paper, we propose a two-phase hierarchical approach to solve the partitioning problem for TMFPGAs. With the precedence and capacity considerations for both phases, the first phase clusters nodes to reduce the problem size, and the second phase applies a probability-based iterative-improvement approach to minimize cut cost. Experimental results based on the Xilinx TMFPGA architecture show that our algorithm significantly outperforms previous works.

Original languageEnglish
Pages (from-to)364-368
Number of pages5
JournalIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers
StatePublished - 1 Dec 1999
EventProceedings of the 1999 IEEE/ACM International Conference on Computer-Aided Design (ICCAD-99) - San Jose, CA, USA
Duration: 7 Nov 199911 Nov 1999


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