Accelerating the Rate of Astronomical Discovery with GPU-Powered Clusters

TL;DR

This paper reviews how GPU clusters are transforming astronomical research by providing faster computation, discusses current adoption trends, and explores opportunities and challenges with new GPU supercomputers like gSTAR.

Contribution

It provides an overview of GPU use in astronomy, highlighting adoption trends and discussing the potential of GPU clusters for accelerating discoveries.

Findings

GPU computing enables significant speed-ups in astronomical data processing

Adoption of GPUs in astronomy is increasing rapidly

GPU clusters like gSTAR offer new opportunities for research acceleration

Abstract

In recent years, the Graphics Processing Unit (GPU) has emerged as a low-cost alternative for high performance computing, enabling impressive speed-ups for a range of scientific computing applications. Early adopters in astronomy are already benefiting in adapting their codes to take advantage of the GPU's massively parallel processing paradigm. I give an introduction to, and overview of, the use of GPUs in astronomy to date, highlighting the adoption and application trends from the first ~100 GPU-related publications in astronomy. I discuss the opportunities and challenges of utilising GPU computing clusters, such as the new Australian GPU supercomputer, gSTAR, for accelerating the rate of astronomical discovery.