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Document Type:Latin Dissertation
Language of Document:English
Record Number:55327
Doc. No:TL25281
Call number:‭1462190‬
Main Entry:Rodrigo A. Urra
Title & Author:Scalable ray tracing with multiple GPGPUsRodrigo A. Urra
College:Rochester Institute of Technology
Date:2009
Degree:M.S.
student score:2009
Page No:94
Abstract:<?Pub Inc> Rapid development in the field of computer graphics over the last 40 years has brought forth different techniques to render scenes. Rasterization is today's most widely used technique, which in its most basic form sequentially draws thousands of polygons and applies texture on them. Ray tracing is an alternative method that mimics light transport by using rays to sample a scene in memory and render the color found at each ray's scene intersection point. Although mainstream hardware directly supports rasterization, ray tracing would be the preferred technique due to its ability to produce highly crisp and realistic graphics, if hardware were not a limitation. Making an immediate hardware transition from rasterization to ray tracing would have a severe impact on the computer graphics industry since it would require redevelopment of existing 3D graphics-employing software, so any transition to ray tracing would be gradual. Previous efforts to perform ray tracing on mainstream rasterizing hardware platforms with a single processor have performed poorly. This thesis explores how a multiple GPGPU system can be used to render scenes via ray tracing. A ray tracing engine and API groundwork was developed using NVIDIA's CUDA (Compute Unified Device Architecture) GPGPU programming environment and was used to evaluate performance scalability across a multi-GPGPU system. This engine supports triangle, sphere, disc, rectangle, and torus rendering. It also allows independent activation of graphics features including procedural texturing, Phong illumination, reflections, translucency, and shadows. Correctness of rendered images validates the ray traced results, and timing of rendered scenes benchmarks performance. The main test scene contains all object types, has a total of 32 objects, and applies all graphics features. Ray tracing this scene using two GPGPUs outperformed the single-GPGPU and single-CPU systems, yielding respective speedups of up to 1.8 and 31.25. The results demonstrate how much potential exists in treating a modern dual-GPU architecture as a dual-GPGPU system in order to facilitate a transition from rasterization to ray tracing.
Subject:Applied sciences; CUDA; GPGPUs; Graphics; Multiprocessors; Ray casting; Ray tracing; Electrical engineering; Computer science; 0984:Computer science; 0544:Electrical engineering
Added Entry:R. Melton
Added Entry:Rochester Institute of Technology