## Abstract

One of the most efficient non-perturbative methods for the calculation of thermal properties of quantum systems is the Hybrid Monte Carlo algorithm, as evidenced by its use in large-scale lattice quantum chromodynamics calculations. The performance of this algorithm is determined by the speed at which the fermion operator is applied to a given vector, as it is the central operation in the preconditioned conjugate gradient iteration. We study a simple implementation of these operations for the fermion matrix of the Hubbard model in d+1 spacetime dimensions, and report a performance comparison between a 2.66 GHz Intel Xeon E5430 CPU and an NVIDIA Tesla C1060 GPU using double-precision arithmetic. We find speedup factors ranging between 30 and 350 for d=1, and in excess of 40 for d=3. We argue that such speedups are of considerable impact for large-scale simulational studies of quantum many-body systems.

Original language | English |
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Pages (from-to) | 1651-1656 |

Number of pages | 6 |

Journal | Computer Physics Communications |

Volume | 182 |

Issue number | 8 |

DOIs | |

Publication status | Published - Aug 2011 |

MoE publication type | A1 Journal article-refereed |

## Keywords

- Graphics processing units
- Quantum many-body systems
- Quantum Monte Carlo