Accelerating Quantum Monte Carlo via Graphics Processing Units

The Calogero-Sutherland model describes a system of particles on a ring with weakly decaying inverse-distance-square-law interactions. The interaction potential must be treated as long range and thus exact simulation studies of its finite temperature properties have been limited to small systems consisting of few particles. We report on a new path Integral quantum Monte Carlo algorithm that exploits the extreme parallelism of Graphics Processing Units to dramatically reduce the computational time of simulations. Speedup factors of up to 500 times allow us to explore finite temperature observables for a range of interaction strengths. While the model itself is of great interest due to its exactly solvable nature, the algorithm is model agnostic and may be particularly useful when applied to experimentally relevant models of high density superfluids.