@article{DAI2011, 
author = {Hui DAI and Qiang ZHOU and Jinian BIAN},
title = {Markov Clustering-Based Placement Algorithm for Hierarchical FPGAs},
year = {2011},
journal = {Tsinghua Science and Technology},
volume = {16},
number = {1},
pages = {62-68},
keywords = {hierarchical FPGAs, Markov chain clustering, placement},
url = {https://www.sciopen.com/article/10.1016/S1007-0214(11)70010-4},
doi = {10.1016/S1007-0214(11)70010-4},
abstract = {Divide-and-conquer methods for FPGA placement algorithms including partition-based and cluster-based algorithms have shown the importance of good quality-runtime trade-off. This paper describes a cluster-based FPGA placement algorithm targeted to a new commercial hierarchical FPGA device. The algorithm is based on a Markov clustering algorithm that defines a sequence of stochastic matrices operating on a generating matrix from the input FPGA circuit netlist. The core of the algorithm tightly couples a Markov clustering process with a multilevel placement process. Tests show its excellent adaptability to hierarchical FPGAs. The average wirelength results produced by the algorithm are 22.3% shorter than the results produced by the current hierarchical FPGA placer.}
}