Parallel accelerated isocontouring for out-of-core visualization

Author

Bajaj, C.L. ; Pascucci, V. ; Thompson, D. ; Zhang, X.Y.

Author_Institution

Dept. of Comput. Sci., Texas Univ., Austin, TX, USA

fYear

1999

fDate

26-26 Oct. 1999

Firstpage

97

Lastpage

122

Abstract

We introduce a scheme for static analysis that allows us to partition large geometric datasets at multiple levels of granularity to achieve both load balancing in parallel computations and minimal access to secondary memory in out-of-core computations. The idea is illustrated and fully exploited for the case of isosurface extraction, but extendible to a class of algorithms based on a small set of parameters and for which an appropriate static analysis can be performed.

Keywords

Cray computers; computational complexity; computational geometry; data visualisation; feature extraction; parallel algorithms; resource allocation; system monitoring; very large databases; visual databases; granularity; isosurface extraction; large geometric dataset partitioning; load balancing; minimal access; out-of-core computations; out-of-core visualization; parallel accelerated isocontouring; parallel computations; secondary memory; static analysis; Acceleration; Algorithm design and analysis; Data mining; Data preprocessing; Data visualization; Isosurfaces; Load management; Partitioning algorithms; Performance analysis; Tree data structures;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel Visualization and Graphics Symposium, 1999. Proceedings. 1999 IEEE`

Conference_Location

San Francisco, CA, USA

Print_ISBN

0-7803-5901-1

Type

conf

DOI

10.1109/PVGS.1999.810144

Filename

810144