Accelerating spherical harmonic transforms for a large number of sky maps

TL;DR

This paper introduces a new, efficient scheme for spherical harmonic transforms optimized for large numbers of sky maps, significantly accelerating computations on both CPU and GPU platforms.

Contribution

The authors develop a novel scheme for spherical harmonic transforms that outperforms existing methods in speed, supporting both CPU and GPU computations for large-scale sky map analysis.

Findings

2-10 times speedup on CPU

up to 30 times speedup on GPU

Open source implementation available

Abstract

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.