Abstract
Current GPU computational power enables the execution of complex and parallel algorithms, such as ray tracing techniques supported by kD-trees for 3D scene rendering in real time. This work describes in detail the study and implementation of eight different kD-tree traversal algorithms using the parallel framework NVIDIA Compute Unified Device Architecture, in order to point their pros and cons regarding performance, memory consumption, branch divergencies and scalability on multiple GPUs. In addition, two new algorithms are proposed by the authors based on this analysis, aiming to performance improvement. Both of them are capable of reaching speedup gains up to 3 × when compared to recent and optimized parallel traversal implementations. As a consequence, interactive frame rates are possible for scenes with 1,408 × 768 pixels of resolution and 3.6 million primitives.
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