Abstract

Population annealing is a novel Monte Carlo algorithm designed for simulations of systems of statistical mechanics with rugged free-energy landscapes. We discuss a realization of the algorithm for the use on a hybrid computing architecture combining CPUs and GPGPUs. The particular advantage of this approach is that it is fully scalable up to many thousands of threads. We report on applications of the developed realization to several interesting problems, in particular the Ising and Potts models, and review applications of population annealing to further systems.

Date

2018

Authors

Lev Shchur, Lev Barash, Martin Weigel

Journal

Supercomputing: 4th Russian Supercomputing Days, RuSCDays 2018, Moscow, Russia, September 24–25, 2018, Revised Selected Papers

Volume

965

Pages

354

Publisher

Springer