Cosmological Calculations on the GPU

TL;DR

This paper demonstrates significant speed-ups in cosmological calculations by implementing two key algorithms on GPUs using CUDA, enabling efficient processing of large datasets from upcoming survey telescopes.

Contribution

The paper introduces GPU-based implementations of two cosmological calculations, achieving up to 180x faster performance than CPU counterparts.

Findings

GPU implementation yields 10-180x speed-up

Code is publicly available for community use

Applicable to large-scale cosmological data analysis

Abstract

Cosmological measurements require the calculation of nontrivial quantities over large datasets. The next generation of survey telescopes (such as DES, PanSTARRS, and LSST) will yield measurements of billions of galaxies. The scale of these datasets, and the nature of the calculations involved, make cosmological calculations ideal models for implementation on graphics processing units (GPUs). We consider two cosmological calculations, the two-point angular correlation function and the aperture mass statistic, and aim to improve the calculation time by constructing code for calculating them on the GPU. Using CUDA, we implement the two algorithms on the GPU and compare the calculation speeds to comparable code run on the CPU. We obtain a code speed-up of between 10 - 180x faster, compared to performing the same calculation on the CPU. The code has been made publicly available.