GPUmonty : A GPU-accelerated Relativistic Monte Carlo Radiative Transfer Code

Read full text
Authors: Pedro Naethe Motta, Rodrigo Nemmen, Abhishek V. Joshi
Cited by: 1
References: 31

Abstract

Abstract We introduce GPUmonty , a CUDA/C-based Monte Carlo radiative transfer code accelerated using graphics processing units (GPUs). GPUmonty derives from the CPU-based code grmonty and offloads the most computationally expensive stages of the calculation—superphoton generation, sampling, tracking, and scattering—to the GPU. Whereas grmonty handles photons sequentially, GPUmonty processes large numbers of superphotons concurrently, leveraging the single-instruction, multiple-thread execution model of modern GPUs. Benchmarks demonstrate a speedup of about 12× relative to the original CPU implementation on a single GPU, with runtime limited primarily by register pressure rather than compute or memory bandwidth saturation. We validate the implementation through analytic tests for a optically thin synchrotron sphere, as well as comparisons with igrmonty for scattering synchrotron sphere and general relativistic magnetohydrodynamic simulation data. Relative errors remain below a percent level, and convergence is consistent with the expected N s − 1 / 2 Monte Carlo scaling. By significantly reducing computational costs, GPUmonty enables the extensive parameter space surveys and faster spectra modeling required to interpret horizon-scale observations of supermassive black holes. GPUmonty is publicly available under the GNU (GNU's Not Unix) General Public License.

Fields of Study & Subjects

Particle Accelerators and Free-Electron Lasers Particle physics theoretical and experimental studies Advanced X-ray Imaging Techniques

Publication details

Journal / source
The Astrophysical Journal
Publisher
American Astronomical Society
Volume
1001
Issue
2
Pages
148–148
Publication date
14 April 2026
Language
EN