An Efficiently Hardware-Software Partitioning for Embedded Multiprocessor FPGA Systems

@inproceedings{Lee2007AnEH,
  title={An Efficiently Hardware-Software Partitioning for Embedded Multiprocessor FPGA Systems},
  author={Trong-Yen Lee and Yang-Hsin Fan and Yu-Min Cheng and Chia-Chun Tsai and Rong-Shue Hsiao},
  booktitle={IMECS},
  year={2007}
}
This work proposes a hardware-software partitioning approach named GHO to solve the partitioning issue for embedded multiprocessor FPGA systems. GHO adopts genetic algorithm and hardware-oriented partition to improve the partitioning result with faster execution time, smaller memory size and higher slice usage under satisfied system constraints. Two experimental results demonstrate that GHO is feasible for solving the hardware-software partition for embedded multiprocessor FPGA systems.