Implementing and Evaluating CPU/GPU Real-Time Ray Tracing Solutions

Ray tracing is a popular algorithm used to simulate the behavior of light and is commonly used to render images with high levels of visual realism. Modern multicore CPUs and many-core GPUs can take advantage of the parallel nature of ray tracing to accelerate the rendering process and produce new im...

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Bibliographic Details
Main Author: Norgren, David
Format: Others
Language:English
Published: Mälardalens högskola, Akademin för innovation, design och teknik 2016
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-32076
Description
Summary:Ray tracing is a popular algorithm used to simulate the behavior of light and is commonly used to render images with high levels of visual realism. Modern multicore CPUs and many-core GPUs can take advantage of the parallel nature of ray tracing to accelerate the rendering process and produce new images in real-time. For non-specialized hardware however, such implementations are often limited to low screen resolutions, simple scene geometry and basic graphical effects. In this work, a C++ framework was created to investigate how the ray tracing algorithm can be implemented and accelerated on the CPU and GPU, respectively. The framework is capable of utilizing two third-party ray tracing libraries, Intel’s Embree and NVIDIA’s OptiX, to ray trace various 3D scenes. The framework also supports several effects for added realism, a user controlled camera and triangle meshes with different materials and textures. In addition, a hybrid ray tracing solution is explored, running both libraries simultaneously to render subsections of the screen. Benchmarks performed on a high-end CPU and GPU are finally presented for various scenes and effects. Throughout these results, OptiX on a Titan X performed better by a factor of 2-4 compared to Embree running on an 8-core hyperthreaded CPU within the same price range. Due to this imbalance of the CPU and GPU along with possible interferences between the libraries, the hybrid solution did not give a significant speedup, but created possibilities for future research.