Parallelizing the Hamiltonian Computation in DQMC Simulations: Checkerboard Method for Sparse Matrix Exponentials on Multicore and GPU

@article{Lee2012ParallelizingTH,
  title={Parallelizing the Hamiltonian Computation in DQMC Simulations: Checkerboard Method for Sparse Matrix Exponentials on Multicore and GPU},
  author={Che-Rung Lee and Zhi-Hung Chen and Quey-Liang Kao},
  journal={2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum},
  year={2012},
  pages={1889-1897}
}
Determinant Quantum Monte Carlo (DQMC) simulation is one of few numerical methods that can explore the micro properties of fermions, which has many technically important applications in chemistry and material science. Conventionally, its parallelization relies on parallel Monte Carlo method, whose speedup is limited by the thermalization process and the underlying matrix computation. To achieve better performance, fine-grained parallelization on its numerical kernel is essential to utilize the… CONTINUE READING

Citations

Publications citing this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 17 REFERENCES

Minimal split checkerboard methods for exponentiating sparse matrices and their applications in quantum mechanics

  • C.-R. Lee
  • under submission, .
  • 2011
2 Excerpts

Determinant quantum Monte Carlo simulations for strongly correlated electron systems

  • C.-R. Lee, I.-H. Chung, Z. Bai
  • IPDPS, .
  • 2010
2 Excerpts

Similar Papers

Loading similar papers…