Fast vectorized algorithm for the Monte Carlo Simulation of the Random Field Ising Model

TL;DR

This paper introduces a highly efficient vectorized algorithm for simulating the 3D random field Ising model, significantly increasing computational speed through multi-spin coding and parallel processing.

Contribution

It presents a novel, fast vectorized algorithm that simulates multiple systems simultaneously, achieving unprecedented update speeds on high-performance hardware.

Findings

Achieves 184 million spin updates per second on Cray YMP.

Optimized version reaches 242 million updates for smaller field strengths.

Demonstrates the effectiveness of multi-spin coding in large-scale simulations.

Abstract

An algoritm for the simulation of the 3--dimensional random field Ising model with a binary distribution of the random fields is presented. It uses multi-spin coding and simulates 64 physically different systems simultaneously. On one processor of a Cray YMP it reaches a speed of 184 Million spin updates per second. For smaller field strength we present a version of the algorithm that can perform 242 Million spin updates per second on the same machine.