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The performance of the Hybrid Monte Carlo algorithm is determined by thespeed of sparse matrix-vector multiplication within the context ofpreconditioned conjugate gradient iteration. We study these operations asimplemented for the fermion matrix of the Hubbard model in d+1 space-timedimensions, and report a performance comparison between a 2.66 GHz Intel XeonE5430 CPU and an NVIDIA Tesla C1060 GPU using double-precision arithmetic. Wefind speedup factors ranging between 30-350 for d = 1, and in excess of 40 ford = 3. We argue that such speedups are of considerable impact for large-scalesimulational studies of quantum many-body systems.

Toward large-scale Hybrid Monte Carlo simulations of the Hubbard model on graphics processing units