Author

Brian Wood

Date of Award

2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Chair

Timothy Newman

Committee Member

Ramazan Aygun

Committee Member

Heggere S. Ranganath

Committee Member

Mary Ellen Weisskopf

Committee Member

Earl Wells

Subject(s)

Information visualization, Data compression (Computer science), Computer graphics, High performance computing

Abstract

This dissertation focuses on increasing isosurfacing speed through novel compression approaches. The compression occurs on a cell-by-cell basis during isosurface extraction, as opposed to compressing the mesh in a post-processing step. The compression is applied to isosurfacing on cluster computers, and it postpones scalability plateauing of prior parallel isosurfacers by reducing communication on cluster computers (versus the prior state of the art). A novel view-dependent isosurface mesh decompressor and improved isosurface orientation estimator for sparse datasets via quadratic splines fit to tetrahedral decompositions of the datasets are also described. Experimental results for all efforts, which quantify their effectiveness, are also presented.

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