Random Number Generators: A Survival Guide for Large Scale Simulations

TL;DR

This paper provides guidance on selecting and using pseudo-random number generators effectively for large-scale, parallel Monte Carlo simulations across various computing systems.

Contribution

It offers a practical overview of pseudo-random number generation tailored for parallel and large-scale simulation environments.

Findings

Guidelines for choosing suitable random number generators for parallel systems

Discussion of challenges in large-scale random number generation

Strategies to ensure statistical quality in parallel simulations

Abstract

Monte Carlo simulations are an important tool in statistical physics, complex systems science, and many other fields. An increasing number of these simulations is run on parallel systems ranging from multicore desktop computers to supercomputers with thousands of CPUs. This raises the issue of generating large amounts of random numbers in a parallel application. In this lecture we will learn just enough of the theory of pseudo random number generation to make wise decisions on how to choose and how to use random number generators when it comes to large scale, parallel simulations.