| Issue |
A&A
Volume 672, April 2023
|
|
|---|---|---|
| Article Number | A83 | |
| Number of page(s) | 20 | |
| Section | Numerical methods and codes | |
| DOI | https://doi.org/10.1051/0004-6361/202346015 | |
| Published online | 04 April 2023 | |
Fast correlation function calculator
A high-performance pair-counting toolkit★
Institute of Physics, Laboratory of Astrophysics, École Polytechnique Fédérale de Lausanne (EPFL), Observatoire de Sauverny,
1290
Versoix, Switzerland
e-mail: cheng.zhao@epfl.ch
Received:
29
January
2023
Accepted:
24
February
2023
Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.
Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simulation catalogues has become a challenge. High-efficiency pair-counting codes are thus in great demand.
Methods. We introduce different data structures and algorithms that can be used for pair-counting problems, and perform comprehensive benchmarks to identify the most efficient algorithms for real-world cosmological applications. We then describe the three levels of parallelisms used by FCFC, SIMD, OpenMP, and MPI, and run extensive tests to investigate the scalabilities. Finally, we compare the efficiency of FCFC with alternative pair-counting codes.
Results. The data structures and histogram update algorithms implemented in FCFC are shown to outperform alternative methods. FCFC does not benefit greatly from SIMD because the bottleneck of our histogram update algorithm is mainly cache latency. Nevertheless, the efficiency of FCFC scales well with the numbers of OpenMP threads and MPI processes, even though speedups may be degraded with over a few thousand threads in total. FCFC is found to be faster than most (if not all) other public pair-counting codes for modern cosmological pair-counting applications.
Key words: methods: data analysis / methods: numerical / techniques: miscellaneous / large-scale structure of Universe
The fast correlation function calculator is publicly available at https://github.com/cheng-zhao/FCFC
© The Authors 2023
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.