Reducing thread divergence in a GPU-accelerated branch-and-bound algorithm

@article{Chakroun2013ReducingTD,
  title={Reducing thread divergence in a GPU-accelerated branch-and-bound algorithm},
  author={Imen Chakroun and Mohand-Said Mezmaz and Nouredine Melab and Ahc{\`e}ne Bendjoudi},
  journal={Concurrency and Computation: Practice and Experience},
  year={2013},
  volume={25},
  pages={1121-1136}
}
In this paper, we address the design and implementation of graphical processing unit (GPU)-accelerated branch-and-bound algorithms (B&B) for solving flow-shop scheduling optimization problems (FSP). Such applications are CPU-time consuming and highly irregular. On the other hand, GPUs are massively multithreaded accelerators using the single instruction multiple data model at execution. A major issue that arises when executing on GPU, a B&B applied to FSP is thread or branch divergence. Such… CONTINUE READING
Highly Cited
This paper has 44 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 1 time over the past 90 days. VIEW TWEETS

Citations

Publications citing this paper.
Showing 1-10 of 22 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 20 references

Similar Papers

Loading similar papers…