可配置的数据预取方案,用于大规模卷数据的交互式可视化

Byungil Jeong, P. Navrátil, K. Gaither, G. Abram, Gregory P. Johnson
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引用次数: 3

摘要

本文提出了一种新的数据预取和内存管理方案,以支持基于gpu的等值面提取的大规模体数据集的交互式可视化。我们的动态核心方法使用跨空间点阵数据结构来预测和预取等值面查询所需的数据集部分,以管理应用程序级卷数据缓存,并确保并行执行的负载平衡。我们还提出了一个GPU内存管理方案,提高了等值面提取和渲染性能。通过这些技术,我们实现了优于其他核心算法的渲染性能,同时使用了更少的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Configurable data prefetching scheme for interactive visualization of large-scale volume data
This paper presents a novel data prefetching and memory management scheme to support interactive visualization of large-scale volume datasets using GPU-based isosurface extraction. Our dynamic in-core approach uses a span-space lattice data structure to predict and prefetch the portions of a dataset that are required by isosurface queries, to manage an application-level volume data cache, and to ensure load-balancing for parallel execution. We also present a GPU memory management scheme that enhances isosurface extraction and rendering performance. With these techniques, we achieve rendering performance superior to other in-core algorithms while using dramatically fewer resources.
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