High Performance Stingray: fast spectral timing for all
| Authors |
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| Publication date | 2025 |
| Book title | 33rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing : PDP 2025 |
| Book subtitle | 12-14 March 2025, Turin, Italy : proceedings |
| ISBN |
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| ISBN (electronic) |
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| Event | 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2025 |
| Pages (from-to) | 459-463 |
| Number of pages | 5 |
| Publisher | Piscataway, NJ: IEEE Computer Society |
| Organisations |
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| Abstract |
Celestial objects are known to be change in brightness over time, driven by a diverse combination of physical processes, whose time scales range from sub-milliseconds to billions of years. Stingray is an open-source Python package that brings advanced time series analysis techniques to the astronomical community, with a focus on high-energy astrophysics, but built on top of general-purpose classes and methods that are designed to be easily adapted and extended to other use cases. We describe the work being done to adapt Stingray to the analysis of large data archives. In particular, we measure the performance and scalability of Stingray and use parallel computing to speed up selected parts of the code. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1109/PDP66500.2025.00071 |
| Other links | https://www.proceedings.com/80132.html https://www.scopus.com/pages/publications/105005026849 |
| Downloads |
High_Performance_Stingray_fast_spectral_timing_for_all
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