并行分布式,gpu加速,先进的照明计算大规模体积可视化

Min Shih, S. Rizzi, J. Insley, T. Uram, V. Vishwanath, M. Hereld, M. Papka, K. Ma
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引用次数: 12

摘要

许多研究人员已经证明了将先进的照明模型应用于体可视化的好处。然而,对于并行分布式GPU计算环境,没有有效的可扩展全局照明计算算法。提出了一种并行、数据分布式、gpu加速的高级光照体绘制算法。我们的方法具有可调的软阴影,以增强对复杂空间结构和关系的感知。对于光照计算,我们的设计有效地避免了gpu之间的数据交换。在使用多达128个GPU的GPU集群上进行性能评估,显示GPU数量和卷数据大小均可扩展的渲染性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel distributed, GPU-accelerated, advanced lighting calculations for large-scale volume visualization
The benefits of applying advanced illumination models to volume visualization have been demonstrated by many researchers. For a parallel distributed, GPU computing environment, however, there is no efficient algorithm for scalable global illumination calculations. This paper presents a parallel, data-distributed and GPU-accelerated algorithm for volume rendering with advanced lighting. Our approach features tunable soft shadows for enhancing perception of complex spatial structures and relationships. For lighting calculations, our design effectively avoids data exchange among GPUs. Performance evaluation on a GPU cluster using up to 128 GPUs shows scalable rendering performance, with both the number of GPUs and volume data size.
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