Pseudo-random number generators for Monte Carlo simulations on Graphics Processing Units

TL;DR

This paper implements and compares various pseudo-random number generators on GPUs, demonstrating significant speed-ups over CPUs and identifying RANLUX as most suitable for Monte Carlo simulations.

Contribution

It presents GPU implementations of multiple pseudo-random generators and evaluates their performance, highlighting RANLUX's suitability for high-energy physics simulations.

Findings

Speed-up factor of hundreds of times compared to CPU

RANLUX identified as most appropriate for GPU Monte Carlo simulations

Performance results for various generators on GPU and CPU

Abstract

Basic uniform pseudo-random number generators are implemented on ATI Graphics Processing Units (GPU). The performance results of the realized generators (multiplicative linear congruential (GGL), XOR-shift (XOR128), RANECU, RANMAR, RANLUX and Mersenne Twister (MT19937)) on CPU and GPU are discussed. The obtained speed-up factor is hundreds of times in comparison with CPU. RANLUX generator is found to be the most appropriate for using on GPU in Monte Carlo simulations. The brief review of the pseudo-random number generators used in modern software packages for Monte Carlo simulations in high-energy physics is present.