Papers › Accelerating spherical harmonic transforms for a large number of sky maps
Accelerating spherical harmonic transforms for a large number of sky maps
Chi Tian, Siyu Li, Hao Liu
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
The spherical harmonic transform is a powerful tool in the analysis of spherical data sets, such as the cosmic microwave background data. In this work, we present a new scheme for the spherical harmonic transforms that supports both CPU and GPU computations, which is specially efficient on a large number of sky maps. By comparing our implementation with the standard Libsharp-HEALPix program, we demonstrate 2-10 times speedup for the CPU implementation, and up to 30 times speedup when a state-of-the-art GPU is employed. This new scheme's software package is available via an open source GitHub repository.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections