Parallel random number generation with AWS Graviton3 based Amazon EC2 instances

Pseudo-random numbers are often used in scientific computing such as the Monte Carlo Simulations or the Quantum Inspired Optimization. Requirements for a parallel random number generator running in the modern multi-core vector environment are more stringent than those for sequential random number generators. As well as passing the usual quality tests, the output of the parallel random number generator must be verifiable and reproducible throughout the concurrent execution.

We propose a family of pseudo-random generators based on the Permuted Congruential Generator algorithm. These generators utilize the SVE2 instruction set available in the AWS Graviton3 processors. Besides demonstrating good single core performance, the generators scale easily across many processor cores and multiple distributed nodes. We provide performance and parallel speedup analysis, as well as comparisons with implementations based on other modern instruction set architectures.