GPU implementation of a ray-surface intersection algorithm in CUDA (Compute Unified Device Architecture)

TL;DR

This paper presents a CUDA-based GPU implementation of a line-segment and surface-triangle intersection algorithm, optimized for efficiency and scalability, with accompanying software documentation and Python API for engineering applications.

Contribution

It introduces an open-source, GPU-accelerated intersection algorithm with detailed documentation and Python integration, improving performance over CPU-based methods.

Findings

Significantly faster than CPU implementations

Scalable for large-scale engineering problems

Provides reusable software for diverse applications

Abstract

These notes accompany the open-source code published in GitHub which implements a GPU-based line-segment, surface-triangle intersection algorithm in CUDA. It mentions some relevant works and discusses issues specific to this implementation. The goal is to provide software documentation and greater clarity on collision buffer management which is sometimes omitted in online literature. For real-world applications, CPU-based implementations of the test are often deemed too slow to be useful. In contrast, the code described here targets Nvidia GPU devices and offers a solution that is vastly more efficient and scalable. The main API is also wrapped in Python. This geometry test is applied in various engineering problems, so the software developed can be reused in new situations.