TY - GEN
T1 - Real-time ray tracing with CUDA
AU - Shih, Min
AU - Chiu, Yung Feng
AU - Chen, Ying Chieh
AU - Chang, Chun Fa
PY - 2009
Y1 - 2009
N2 - The graphics processors (GPUs) have recently emerged as a low-cost alternative for parallel programming. Since modern GPUs have great computational power as well as high memory bandwidth, running ray tracing on them has been an active field of research in computer graphics in recent years. Furthermore, the introduction of CUDA, a novel GPGPU architecture, has removed several limitations that the traditional GPU-based ray tracing suffered. In this paper, an implementation of high per formance CUDA ray tracing is demonstrated. We focus on the perfor mance and show how our design choices in various optimization lead to an implementation that outperforms the previous works. For reasonably complex scenes with simple shading, our implementation achieves the performance of 30 to 43 million traced rays per second. Our implementation also includes the effects of recursive specular reflection and refraction, which were less discussed in previous GPU-based ray tracing works.
AB - The graphics processors (GPUs) have recently emerged as a low-cost alternative for parallel programming. Since modern GPUs have great computational power as well as high memory bandwidth, running ray tracing on them has been an active field of research in computer graphics in recent years. Furthermore, the introduction of CUDA, a novel GPGPU architecture, has removed several limitations that the traditional GPU-based ray tracing suffered. In this paper, an implementation of high per formance CUDA ray tracing is demonstrated. We focus on the perfor mance and show how our design choices in various optimization lead to an implementation that outperforms the previous works. For reasonably complex scenes with simple shading, our implementation achieves the performance of 30 to 43 million traced rays per second. Our implementation also includes the effects of recursive specular reflection and refraction, which were less discussed in previous GPU-based ray tracing works.
KW - CUDA
KW - GPU Computing
KW - Multithreaded Architectures
KW - Programmable Graphics Hardware
KW - Ray Tracing
UR - http://www.scopus.com/inward/record.url?scp=70349107292&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349107292&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-03095-6_32
DO - 10.1007/978-3-642-03095-6_32
M3 - Conference contribution
AN - SCOPUS:70349107292
SN - 3642030947
SN - 9783642030949
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 327
EP - 337
BT - Algorithms and Architectures for Parallel Processing - 9th International Conference, ICA3PP 2009, Proceedings
T2 - 9th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2009
Y2 - 8 June 2009 through 11 June 2009
ER -