Paper Info
Title
Shared-Memory Parallel Computation Of Morse-Smale Complexes With Improved Accuracy
Abstract
Topological techniques have proven to be a powerful tool in the analysis and visualization of large-scale scientific data. In particular, the Morse-Smale complex and its various components provide a rich framework for robust feature definition and computation. Consequently, there now exist a number of approaches to compute Morse-Smale complexes for large-scale data in parallel. However, existing techniques are based on discrete concepts which produce the correct topological structure but are known to introduce grid artifacts in the resulting geometry. Here, we present a new approach that combines parallel streamline computation with combinatorial methods to construct a high-quality discrete Morse-Smale complex. In addition to being invariant to the orientation of the underlying grid, this algorithm allows users to selectively build a subset of features using high-quality geometry. In particular, a user may specifically select which ascending/descending manifolds are reconstructed with improved accuracy, focusing computational effort where it matters for subsequent analysis. This approach computes Morse-Smale complexes for larger data than previously feasible with significant speedups. We demonstrate and validate our approach using several examples from a variety of different scientific domains, and evaluate the performance of our method.
Year
DOI
Venue
2019
10.1109/TVCG.2018.2864848
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
Keywords
Field
DocType
Morse complex, Parallel Computation, Topology, Accurate Geometry
Shared memory,Visualization,Computer science,Feature extraction,Theoretical computer science,Robustness (computer science),Invariant (mathematics),Manifold,Grid,Computation
Journal
Volume
Issue
ISSN
25
1
1077-2626
Citations 
PageRank 
References 
6
0.42
9
Authors
3
Name
Order
Citations
PageRank
Attila Gyulassy145323.11
Peer-Timo Bremer2144682.47
Valerio Pascucci33241192.33