@inbook{cbca55c67a10418ea16ace5660dd1b74,
title = "Delivering Faster Results Through Parallelisation and GPU Acceleration",
abstract = "The rate of scientific discovery depends on the speed at which accurate results and analysis can be obtained. The use of parallel co-processors such as Graphical Processing Units (GPUs) is becoming more and more important in meeting this demand as improvements in serial data processing speed become increasingly difficult to sustain. However, parallel data processing requires more complex programming compared to serial processing. Here we present our methods for parallelising two pieces of scientific software, leveraging multiple GPUs to achieve up to thirty times speed up.",
keywords = "GPU, CUDA, GPU cluster, Parallelisation",
author = "Matthew Newall and Violeta Holmes and Colin Venters and Paul Lunn",
year = "2015",
month = feb,
day = "14",
doi = "10.1007/978-3-319-14654-6_19",
language = "English",
isbn = "978-3-319-14653-9",
volume = "591",
series = "Studies in Computational Intelligence",
publisher = "Springer",
pages = "309--320",
editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",
booktitle = "Intelligent Systems in Science and Information 2014",
address = "United Kingdom",
}