GRTX: Efficient Ray Tracing for 3D Gaussian-Based Rendering

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Authors: Junseo Lee, Sangyun Jeon, Jungi Lee, Junyong Park, Jaewoong Sim
Cited by: 0

Abstract

3D Gaussian Splatting has gained widespread adoption across diverse applications due to its exceptional rendering performance and visual quality. While most existing methods rely on rasterization to render Gaussians, recent research has started investigating ray tracing approaches to overcome the fundamental limitations inherent in rasterization. However, current Gaussian ray tracing methods suffer from inefficiencies such as bloated acceleration structures and redundant node traversals, which greatly degrade ray tracing performance. In this work, we present GRTX, a set of software and hardware optimizations that enable efficient ray tracing for 3D Gaussian-based rendering. First, we introduce a novel approach for constructing streamlined acceleration structures for Gaussian primitives. Our key insight is that anisotropic Gaussians can be treated as unit spheres through ray space transformations, which substantially reduces BVH size and traversal overhead. Second, we propose dedicated hardware support for traversal checkpointing within ray tracing units. This eliminates redundant node visits during multi-round tracing by resuming traversal from checkpointed nodes rather than restarting from the root node in each subsequent round. Our evaluation shows that GRTX significantly improves ray tracing performance compared to the baseline ray tracing method with a negligible hardware cost.

Fields of Study & Subjects

Computer Graphics and Visualization Techniques 3D Shape Modeling and Analysis Parallel Computing and Optimization Techniques

Publication details

Journal / source
arXiv (Cornell University)
Publication date
28 January 2026
Document type
Preprint