2021/07/12 by Julián Burella Pérez, Pérez, Julián Burella, Sydney Hauke +7 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · #68R99 #Cell Image Analysis Techniques #Computational Geometry (cs.CG) #FOS: Computer and information sciences #G.2.2 #G.4 #Leprosy Research and Treatment #Mathematical Software (cs.MS) #Topological and Geometric Data Analysis #acm:68R99 #cs.CG #cs.MS #msc:68R99
paper · pdf · doi:10.48550/arxiv.2107.05412
18 pages, 7 figures
openalex publication_date 2021/07/12 · arxiv created 2021/08/02 · arxiv updated 2021/08/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We introduce giotto-ph, a high-performance, open-source software package for the computation of Vietoris-Rips barcodes. giotto-ph is based on Morozov and Nigmetov's lockfree (multicore) implementation of Ulrich Bauer's Ripser package. It also contains a re-working of the GUDHI library's implementation of Boissonnat and Pritam's Edge Collapser, which can be used as a pre-processing step to dramatically reduce overall run-times in certain scenarios. Our contribution is twofold: on the one hand, we integrate existing state-of-the-art ideas coherently in a single library and provide Python bindings to the C++ code. On the other hand, we increase parallelization opportunities and improve overall performance by adopting more efficient data structures. Our persistent homology backend establishes a new state of the art, surpassing even GPU-accelerated implementations such as Ripser++ when using as few as 5-10 CPU cores. Furthermore, our implementation of Edge Collapser has fewer software dependencies and improved run-times relative to GUDHI's original implementation.