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KD-Tree Traversal Implementations for Ray Tracing on Massive Multiprocessors: a Comparative Study

机译:大规模多处理器上射线跟踪的KD树遍历实现:比较研究

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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 five different kD-Tree traversal algorithms using the parallel framework NVIDIA Compute Unified Device Architecture (CUDA), in order to point their pros and cons regarding adaptation capability to the chosen architecture. In addition, a new algorithm is proposed by the authors based on this analysis, aiming performance improvement. A performance analysis of the implemented techniques demonstrates that two of these algorithms, once adequately adapted to CUDA architecture, are capable of reaching speedup gains up to 15x when compared to former CPU implementations and up to 4x in comparison to existing and optimized parallel ones. As a consequence, interactive frame rates are possible for scenes with 1376×768 pixels of resolution and 1 million primitives.
机译:目前的GPU计算能力使得能够执行复杂和并行算法,例如KD-Tread支持的光线跟踪技术,用于实时呈现3D场景呈现。这项工作详细描述了使用并行框架NVIDIA计算统一设备架构(CUDA)的五种不同KD树遍历算法的研究和实现,以将其优点和缺点指向所选择的架构的适应能力。此外,作者基于该分析提出了一种新的算法,旨在改进性能。实施技术的性能分析表明,与以前的CPU实现相比,这两个算法中的两个算法一旦适用于CUDA架构,能够达到高达15倍的加速增益,并且与现有和优化的并行平行相比,高达4倍。因此,分辨率为1376×768像素的场景和100万基元的场景可以实现交互式帧速率。

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