Leveraging BC6H Texture Compression and Filtering for Efficient Vector Field Visualization
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The steady advance of compute hardware is accompanied by an ever-steeper amount of data to be processed for visualization. Limited memory bandwidth provides a significant bottleneck to the runtime performance of visualization algorithms while limited video memory requires complex out-of-core loading techniques for rendering large datasets. Data compression methods aim to overcome these limitations, potentially at the cost of information loss. This work presents an approach to the compression of large data for flow visualization using the BC6H texture compression format natively supported, and therefore effortlessly leverageable, on modern GPUs. We assess the performance and accuracy of BC6H for compression of steady and unsteady vector fields and investigate its applicability to particle advection. The results indicate an improvement in memory utilization as well as runtime performance, at a cost of moderate loss in precision.
Description
CCS Concepts: Computing methodologies → Image compression; Graphics processors; Human-centered computing → Visualization
@inproceedings{10.2312:vmv.20231238,
booktitle = {Vision, Modeling, and Visualization},
editor = {Guthe, Michael and Grosch, Thorsten},
title = {{Leveraging BC6H Texture Compression and Filtering for Efficient Vector Field Visualization}},
author = {Oehrl, Simon and Milke, Jan Frieder and Koenen, Jens and Kuhlen, Torsten W. and Gerrits, Tim},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-232-5},
DOI = {10.2312/vmv.20231238}
}