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Image-space decomposition algorithms for sort-first parallel volume rendering of unstructured grids

机译:用于非结构化网格排序优先并行体积渲染的图像空间分解算法

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摘要

Twelve adaptive image-space decomposition algorithms are presented for sort-first parallel direct volume rendering (DVR) of unstructured grids on distributed-memory architectures. The algorithms are presented under a novel taxonomy based on the dimension of the screen decomposition, the dimension of the workload arrays used in the decomposition, and the scheme used for workload-array creation and querying the workload of a region. For the 2D decomposition schemes using 2D workload arrays, a novel scheme is proposed to query the exact number of screen-space bounding boxes of the primitives in a screen region in constant time. A probe-based chains-on-chains partitioning algorithm is exploited for load balancing in optimal 1D decomposition and iterative 2D rectilinear decomposition (RD). A new probe-based optimal 2D jagged decomposition (OJD) is proposed which is much faster than the dynamic-programming based OJD scheme proposed in the literature. The summed-area table is successfully exploited to query the workload of a rectangular region in constant time in both OJD and RD schemes for the subdivision of general 2D workload arrays. Two orthogonal recursive bisection (ORB) variants are adapted to relax the straight-line division restriction in conventional ORB through using the medians-of-medians approach on regular mesh and quadtree superimposed on the screen. Two approaches based on the Hilbert space-filling curve and graph-partitioning are also proposed. An efficient primitive classification scheme is proposed for redistribution in 1D, and 2D rectilinear and jagged decompositions. The performance comparison of the decomposition algorithms is modeled by establishing appropriate quality measures for load-balancing, amount of primitive replication and parallel execution time. The experimental results on a Parsytec CC system using a set of benchmark volumetric datasets verify the validity of the proposed performance models. The performance evaluation of the decomposition algorithms is also carried out through the sort-first parallelization of an efficient DVR algorithm.
机译:提出了十二种自适应图像空间分解算法,用于分布式内存体系结构上非结构化网格的排序优先并行直接体积渲染(DVR)。根据屏幕分解的维数,分解中使用的工作负载数组的大小以及用于工作负载数组创建和查询区域工作负载的方案,在一种新颖的分类法下给出了算法。对于使用2D工作负载数组的2D分解方案,提出了一种新颖的方案,用于在恒定时间内查询屏幕区域中图元的屏幕空间边界框的确切数量。利用基于探针的链上链分区算法在最佳一维分解和迭代二维直线分解(RD)中实现负载平衡。提出了一种新的基于探针的最佳2D锯齿状分解(OJD),其速度比文献中提出的基于动态编程的OJD方案要快得多。成功地利用求和面积表在OJD和RD方案中以恒定时间查询矩形区域的工作量,以细分常规2D工作量阵列。通过使用规则网格上的中位数中值方法和叠加在屏幕上的四叉树,两个正交递归对分(ORB)变体适用于放宽常规ORB中的直线划分限制。还提出了两种基于希尔伯特空间填充曲线和图划分的方法。提出了一种有效的原始分类方案,用于一维,二维直线和锯齿形分解中的重新分布。通过为负载平衡,原始复制量和并行执行时间建立适当的质量度量,对分解算法的性能比较进行建模。在使用一组基准体积数据集的Parsytec CC系统上的实验结果验证了所提出的性能模型的有效性。分解算法的性能评估还通过有效DVR算法的排序优先并行化进行。

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