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DOI: 10.14569/IJACSA.2025.0160205
PDF

Exploiting Ray Tracing Technology Through OptiX to Compute Particle Interactions with Cutoff in a 3D Environment on GPU

Author 1: David Algis
Author 2: Berenger Bramas

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 2, 2025.

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Abstract: Particle interaction simulation is a fundamental method of scientific computing that require high-performance solutions. In this context, computing on graphics processing units (GPUs) has become standard due to the significant performance gains over conventional CPUs. However, since GPUs were originally designed for 3D rendering, they still retain several features that are not fully exploited in scientific computing. One such feature is ray tracing, a powerful technique for rendering 3D scenes. In this paper, we propose exploiting ray tracing technology via OptiX and CUDA to compute particle interactions with a cutoff distance in a 3D environment on GPUs. To this end, we describe algorithmic techniques and geometric patterns for efficiently determining the interaction lists for each particle. Our approach enables the computation of interactions with quasi-linear complexity in the number of particles, eliminating the need to construct a grid of cells or an explicit kd-tree. We compare the performance of our method to a classical grid-based approach and demonstrate that our approach is faster in most cases with non-uniform particle distributions.

Keywords: CUDA; graphics processing unit; high-performance computing; OptiX; particle interactions; ray tracing; scientific computing

David Algis and Berenger Bramas, “Exploiting Ray Tracing Technology Through OptiX to Compute Particle Interactions with Cutoff in a 3D Environment on GPU” International Journal of Advanced Computer Science and Applications(IJACSA), 16(2), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160205

@article{Algis2025,
title = {Exploiting Ray Tracing Technology Through OptiX to Compute Particle Interactions with Cutoff in a 3D Environment on GPU},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160205},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160205},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {David Algis and Berenger Bramas}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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