# Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

arXiv: https://arxiv.org/abs/2403.12345 · HTML: https://mlsanity.com/paper/2403.12345/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Mar 2024.

## Built on by (most cited first, 3 of 3)

- [InSpire: Vision-Language-Action Models with Intrinsic Spatial Reasoning](https://mlsanity.com/paper/2505.13888/) (2025)
- [RISE: Enhancing VLM Image Annotation with Self-Supervised Reasoning](https://mlsanity.com/paper/2508.13229/) (2025)
- [Beyond Backpropagation: Monte Carlo Method Can Train Deep Neural Networks](https://mlsanity.com/paper/2607.08406/) (2026)

## Abstract (arXiv)

OpenMC is an open source Monte Carlo neutral particle transport application that has recently been ported to GPU using the OpenMP target offloading model. We examine the performance of OpenMC at scale on the Frontier, Polaris, and Aurora supercomputers, demonstrating that performance portability has been achieved by OpenMC across all three major GPU vendors (AMD, NVIDIA, and Intel). OpenMC's GPU performance is compared to both the traditional CPU-based version of OpenMC as well as several other state-of-the-art CPU-based Monte Carlo particle transport applications. We also provide historical context by analyzing OpenMC's performance on several legacy GPU and CPU architectures. This work includes some of the first published results for a scientific simulation application at scale on a supercomputer featuring Intel's Max series "Ponte Vecchio" GPUs. It is also one of the first demonstrations of a large scientific production application using the OpenMP target offloading model to achieve high performance on all three major GPU platforms.