DocumentCode :
229073
Title :
Out-of-core visualization of time-varying hybrid-grid volume data
Author :
Min Shih ; Yubo Zhang ; Kwan-Liu Ma ; Sitaraman, Jayanarayanan ; Mavriplis, Dimitri
Author_Institution :
Univ. of California, Davis, Davis, CA, USA
fYear :
2014
fDate :
9-10 Nov. 2014
Firstpage :
93
Lastpage :
100
Abstract :
Traditional computational fluid dynamics (CFD) solvers are usually written for a single gridding paradigm such as structured-Cartesian, structured-body-fitted, or unstructured grids. Each type of mesh paradigms has inherent advantages and disadvantages. Thus, the methods of coupling multiple mesh paradigms have been developed to facilitate the use of different solvers in different part of the computational domain. However, the complex hybrid gridding paradigm poses challenges to rendering calculations for visualizing the data. This paper describes a volume visualization system for time-varying adaptive moving-body CFD datasets, where the grid system consists of unstructured grids near the body surface, coupled with Structured Adaptive Mesh Refinement (SAMR) grid in the off-body domain. We present two approaches to the hybrid-grid volume ray casting: a KD-tree based single-pass algorithm, and a multi-pass algorithm using the depth peeling technique. The system has a three-level memory hierarchy: GPU memory, main memory, and a solid state drive (SSD). Through data caching and prefetching within the memory hierarchy, the latency of time-step swapping can be hidden. Experimental results show that our system allows interactive volume exploration on single-GPU commodity PCs.
Keywords :
computational fluid dynamics; data visualisation; graphics processing units; grid computing; trees (mathematics); CFD solvers; GPU memory; KD-tree; SAMR grid; SSD; computational fluid dynamics; hybrid-grid volume ray casting; multiple mesh paradigms; out-of-core visualization; single gridding paradigm; solid state drive; structured adaptive mesh refinement; time-varying hybrid-grid volume data; volume visualization system; Casting; Data visualization; Graphics processing units; Legged locomotion; Prefetching; Rendering (computer graphics); Runtime;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Large Data Analysis and Visualization (LDAV), 2014 IEEE 4th Symposium on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/LDAV.2014.7013209
Filename :
7013209
Link To Document :
بازگشت