Tuning the Performance of a Computational Persistent Homology Package.

Author: 

Hylton, A
Henselman-Petrusek, G
Sang, J
Short, R

Publication Date: 

May 2019

Journal: 

Software: practice & experience

Last Updated: 

2021-10-19T13:24:02.673+01:00

Issue: 

5

Volume: 

49

DOI: 

10.1002/spe.2678

page: 

885-905

abstract: 

In recent years, persistent homology has become an attractive method for data analysis. It captures topological features, such as connected components, holes, and voids from point cloud data and summarizes the way in which these features appear and disappear in a filtration sequence. In this project, we focus on improving the performance of Eirene, a computational package for persistent homology. Eirene is a 5000-line open-source software library implemented in the dynamic programming language Julia. We use the Julia profiling tools to identify performance bottlenecks and develop novel methods to manage them, including the parallelization of some time-consuming functions on multicore/manycore hardware. Empirical results show that performance can be greatly improved.

Symplectic id: 

1139091

Submitted to ORA: 

Not Submitted

Publication Type: 

Journal Article