Ray tracing method for stereo image synthesis using CUDA

TL;DR

This paper demonstrates a GPU-accelerated ray tracing method for stereo 3D image synthesis using CUDA, highlighting performance considerations and the importance of optimized parallel network structures.

Contribution

It introduces a CUDA-based implementation of ray tracing for stereo 3D visualization, emphasizing data transfer and parallelization strategies for improved performance.

Findings

60% of computation time is spent on the core algorithm

40% of time is spent on data transfer and visualization setup

Proper structuring of parallel GPU networks significantly affects computation speed

Abstract

This paper presents a realization of the approach to spatial 3D stereo of visualization of 3D images with use parallel Graphics processing unit (GPU). The experiments of realization of synthesis of images of a 3D stage by a method of trace of beams on GPU with Compute Unified Device Architecture (CUDA) have shown that 60 % of the time is spent for the decision of a computing problem approximately, the major part of time (40 %) is spent for transfer of data between the central processing unit and GPU for computations and the organization process of visualization. The study of the influence of increase in the size of the GPU network at the speed of computations showed importance of the correct task of structure of formation of the parallel computer network and general mechanism of parallelization. Keywords: Volumetric 3D visualization, stereo 3D visualization, ray tracing, parallel computing on GPU, CUDA