GPU Rasterization for Real-Time Spatial Aggregation over Arbitrary Polygons
GPU Rasterization for Real-Time Spatial Aggregation over Arbitrary Polygons
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DOI：
10.14778/3157794.3157803
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发表时间：
2017-11
期刊：
影响因子：
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通讯作者：
Eleni Tzirita Zacharatou;Harish Doraiswamy;A. Ailamaki;Cláudio T. Silva;J. Freire
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文献类型：
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作者：
Eleni Tzirita Zacharatou;Harish Doraiswamy;A. Ailamaki;Cláudio T. Silva;J. Freire
空间数据的可视化探索在很大程度上依赖于对不同区域的数据进行切片和汇总的空间聚合查询。这些查询包括将数据点与多边形区域相关联的计算密集型多边形点测试，这对可视化工具的响应能力提出了挑战。这一挑战因数据量巨大而变得更加复杂，需要执行大量这样的测试。传统的预聚类方法不适合这种情况，因为它们固定了查询约束，并且只支持矩形区域。另一方面，查询约束在视觉分析系统中以交互方式定义，并且多边形可以是任意形状。在本文中，我们将空间聚集查询转换为一组画布上的绘制操作，并利用图形硬件(GPU)的渲染流水线来实现交互响应时间。我们的技术通过调整画布分辨率来权衡精度和响应时间，甚至可以在与多边形索引结合时提供准确的结果。我们在两个大型真实数据集上对我们的技术进行了评估，与基于索引的方法相比，我们的技术表现出了更好的性能。
Visual exploration of spatial data relies heavily on spatial aggregation queries that slice and summarize the data over different regions. These queries comprise computationally-intensive point-in-polygon tests that associate data points to polygonal regions, challenging the responsiveness of visualization tools. This challenge is compounded by the sheer amounts of data, requiring a large number of such tests to be performed. Traditional pre-aggregation approaches are unsuitable in this setting since they fix the query constraints and support only rectangular regions. On the other hand, query constraints are defined interactively in visual analytics systems, and polygons can be of arbitrary shapes. In this paper, we convert a spatial aggregation query into a set of drawing operations on a canvas and leverage the rendering pipeline of the graphics hardware (GPU) to enable interactive response times. Our technique trades-off accuracy for response time by adjusting the canvas resolution, and can even provide accurate results when combined with a polygon index. We evaluate our technique on two large real-world data sets, exhibiting superior performance compared to index-based approaches.