In this paper, we discuss our experience in implementing homology computation, in particular Betti number calculation in Chapel hypergraph Library (CHGL). Given a dataset represented as a hypergraph, a Betti number for a particular dimension $k$ indicates how many $k$-dimensional `voids' are present in the dataset. Computing Betti number involves various array-centric and linear algebra operations. We demonstrate that implementing these operations in Chapel is both concise and intuitive. In addition, we show that Chapel provides language constructs for implementing parallel and distributed execution of the linear algebra kernels with minimal effort. Syntactically, Chapel provides succinctness of Python, while delivering comparable and better performance than C++-based and Julia-based packages for calculating Betti numbers respectively.
Revised: October 29, 2020 |
Published: July 28, 2020
Citation
Firoz J.S., L. Jenkins, C.A. Joslyn, B.L. Praggastis, E. Purvine, and M.V. Raugas. 2020.Computing Hypergraph Homology in Chapel. In IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW 2020), May 18-22, 2020, New Orleans, LA, 667-670. Piscataway, New Jersey:IEEE.PNNL-SA-152026.doi:10.1109/IPDPSW50202.2020.00112