Component-based Data Layout for Efficient Slicing of Very Large Multidimensional Volumetric Data

Abstract

In this paper, we introduce a new efficient data layout scheme to efficiently handle out-of-core axis-aligned slicing queries of very large multidimensional volumetric data. Slicing is a very useful dimension reduction tool that removes or reduces occlusion problems in visualizing 3D/4D volumetric data sets and that enables fast visual exploration of such data sets. We show that the data layouts based on typical space-filling curves are not optimal for the out-of-core slicing queries and present a novel component-based data layout scheme for a specialized problem domain, in which it is only required to provide fast slicing at every k-th value, for any k > 1. Our component-based data layout scheme provides much faster processing time for any axis-aligned slicing direction at every k-th value, k > 1, requiring less cache memory size and without any replication of data. In addition, the data layout can be generalized to any high dimension.