Accelerating mesh-based Monte Carlo simulations using contemporary graphics ray-tracing hardware
Shijie Yan, Douglas Dwyer, David R. Kaeli, Qianqian Fang

TL;DR
This paper introduces RT-MMC, a GPU-accelerated mesh-based Monte Carlo simulation method that leverages hardware-accelerated ray-tracing to significantly speed up light-tissue interaction modeling, simplifying workflows and improving performance.
Contribution
The paper presents RT-MMC, a novel GPU-based algorithm that uses hardware-accelerated ray-tracing cores to enhance the speed and simplicity of mesh-based Monte Carlo simulations.
Findings
Achieves 1.5x to 4.5x speedups over traditional software methods
Maintains excellent agreement with existing Monte Carlo algorithms
Simplifies simulation workflows by eliminating complex mesh generation
Abstract
Significance: Monte Carlo (MC) methods are the gold-standard for modeling light-tissue interactions due to their accuracy. Mesh-based MC (MMC) offers enhanced precision for complex tissue structures using tetrahedral mesh models. Despite significant speedups achieved on graphics processing units (GPUs), MMC performance remains hindered by the computational cost of frequent ray-boundary intersection tests. Aim: We propose a highly accelerated MMC algorithm, RT-MMC, that leverages the hardware-accelerated ray traversal and intersection capabilities of ray-tracing cores (RT-cores) on modern GPUs. Approach: Implemented using NVIDIA's OptiX platform, RT-MMC extends graphics ray-tracing pipelines towards volumetric ray-tracing in turbid media, eliminating the need for challenging tetrahedral mesh generation while delivering significant speed improvements through hardware acceleration. It…
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · Optical Imaging and Spectroscopy Techniques · Advanced Radiotherapy Techniques
