Scalable Contour Tree Computation by Data Parallel Peak Pruning
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- UOA11-2392
- Type
- D - Journal article
- DOI
-
10.1109/TVCG.2019.2948616
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 0
- Volume
- 0
- Issue
- -
- ISSN
- 1077-2626
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
D - CSE (Computational Science and Engineering)
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper describes a data parallel algorithm for contour tree construction in collaboration with Los Alamos and Lawrence Berkeley Laboratories, with speedups of up to 70x faster than serial, 18x faster than competitors. It won the Best Paper award at Large Data Analysis and Visualization 2016, and ships in the vtk-m multicore visualization toolkit. This enabled Carr’s funding under the Department of Energy / National Nuclear Security Administration Exascale Computing Project (ECP-Alpine), funding normally restricted to US researchers only, with one additional paper accepted and two more in the pipeline, and strong scaling on the world’s #2 supercomputer, Summit.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
