Dense Texture Flow Visualization using Data-Parallel Primitives
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Date
2018
Authors
Journal Title
Journal ISSN
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Publisher
The Eurographics Association
Abstract
Recent trends in supercomputing towards massively threaded on-node processors to increase performance has also introduced fragmented software support. In response to this changing landscape, new scientific visualization packages have been developed to provide a portable framework to exploit this on-node parallelism with data parallel primitives, while also providing a single interface to multiple hardware backends. This necessitates adapting algorithms to the data parallel primitives paradigm. In numerous cases the algorithm is serial, but other times the technique is tied to hardware and needs to be generalized to broadly disseminate. In this work, we present unsteady flow line integral convolution (UFLIC) using only data parallel primitives. Line integral convolution (LIC) is a fundamental flow visualization technique in scientific visualization. LIC and its texture-based variants, are used in fields such as meteorology and computational fluid dynamics to aid practitioners because of its efficient memory usage, strong, visual flow characteristics, and efficient performance. However, in practice performant implementations are GPU shader-based approaches, which limits deployment and adoption. By utilizing VTK-m, our approach is a performant, memory efficient implementation, with the added benefit of portability, with a single implementation across many architectures.
Description
@inproceedings{10.2312:pgv.20181095,
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
editor = {Hank Childs and Fernando Cucchietti},
title = {{Dense Texture Flow Visualization using Data-Parallel Primitives}},
author = {Kim, Mark and Klasky, Scott and Pugmire, David},
year = {2018},
publisher = {The Eurographics Association},
ISSN = {1727-348X},
ISBN = {978-3-03868-054-3},
DOI = {10.2312/pgv.20181095}
}