Accelerating the Rate of Astronomical Discovery with GPU-Powered Clusters
Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, Victoria, Australia
arXiv:1111.5081v1 [astro-ph.IM] (22 Nov 2011)
@article{2011arXiv1111.5081F,
author={Fluke}, C.~J.},
title={"{Accelerating the Rate of Astronomical Discovery with GPU-Powered Clusters}"},
journal={ArXiv e-prints},
archivePrefix={"arXiv"},
eprint={1111.5081},
primaryClass={"astro-ph.IM"},
keywords={Astrophysics – Instrumentation and Methods for Astrophysics},
year={2011},
month={nov},
adsurl={http://adsabs.harvard.edu/abs/2011arXiv1111.5081F},
adsnote={Provided by the SAO/NASA Astrophysics Data System}
}
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.
November 23, 2011 by hgpu
Recent source codes
