End-to-end data reduction and hardware accelerated rendering techniques for visualizing time-varying non-uniform grid volume data

H. Akiba, K. Ma, J. Clyne
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引用次数: 17

Abstract

We present a systematic approach for direct volume rendering terascale-sized data that are time-varying, and possibly non-uniformly sampled, using only a single commodity graphics PC. Our method employs a data reduction scheme that combines lossless, wavelet-based progressive data access with a user-directed, hardware-accelerated data packing technique. Data packing is achieved by discarding data blocks with values outside the data interval of interest and encoding the remaining data in a structure that can be efficiently decoded in the GPU. The compressed data can be transferred between disk, main memory, and video memory more efficiently, leading to more effective data exploration in both spatial and temporal domains. Furthermore, our texture-map based volume rendering system is capable of correctly displaying data that are sampled on a stretched, Cartesian grid. To study the effectiveness of our technique we used data sets generated from a large solar convection simulation, computed on a non-uniform, 504/spl times/504/spl times/2048 grid.
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用于时变非均匀网格体数据可视化的端到端数据缩减和硬件加速渲染技术
我们提出了一种系统的方法,用于直接体渲染时间变化的万亿级数据,并且可能不均匀采样,仅使用单个商品图形PC。我们的方法采用了一种数据约简方案,该方案结合了无损的、基于小波的渐进式数据访问和用户导向的、硬件加速的数据打包技术。数据打包是通过丢弃值在感兴趣的数据间隔之外的数据块,并将剩余数据编码为可以在GPU中有效解码的结构来实现的。压缩后的数据可以更有效地在磁盘、主存储器和显存之间传输,从而在空间和时间域中实现更有效的数据探索。此外,我们基于纹理映射的体渲染系统能够正确显示在拉伸的笛卡尔网格上采样的数据。为了研究我们的技术的有效性,我们使用了在非均匀504/spl次/504/spl次/2048网格上计算的大型太阳对流模拟数据集。
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