2021/06/21 by Michalis Charilaou, Charilaou, Michalis
Computer Science · Mathematics · Physics and Astronomy · #Acceleration #Anisotropy #Computational Physics (physics.comp-ph) #Computational physics #Computational science #Computer graphics (images) #Computer science #Condensed matter physics #Dynamic Monte Carlo method #FOS: Physical sciences #Ferromagnetism #Graphics #Graphics processing unit #Heisenberg model #Magnetic properties of thin films #Mathematics #Matrix Theory and Algorithms #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Monte Carlo method #Parallel computing #Physics #Quantum mechanics #Spins #Statistical Mechanics (cond-mat.stat-mech) #Statistical physics #Theoretical and Computational Physics #cond-mat.mes-hall #cond-mat.stat-mech #physics.comp-ph
paper · pdf · doi:10.48550/arxiv.2106.11286
published in arXiv (Cornell University) (Cornell University) · 4 pages, 3 figures
arxiv created 2021/06/21 · openalex publication_date 2021/06/21 · arxiv updated 2021/06/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
The Monte Carlo method is a powerful technique for computing thermodynamic magnetic states of otherwise unsolvable spin Hamiltonians, but the method becomes computationally prohibitive with increasing number of spins and the simulation of real materials and nanostructures is cumbersome. This paper presents the acceleration of Monte Carlo simulations of the three-dimensional anisotropic Heisenberg model on Graphics-Processing Units (GPU). The GPU implementation of the method presented here provides an acceleration of two orders of magnitude over conventional implementations and enables the simulation of large systems, with any crystal lattice, containing up to 108 spins on a single GPU. This offers the possibility to simulate complex structures and devices that are hundreds of nanometers in size in order to compute their magnetic state at finite temperature with atomistic resolution.