Delivering faster results through parallelisation and GPU acceleration

Matthew Newall, Violeta Holmes, Colin Venters, Paul Lunn

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)309-320
Number of pages12
JournalStudies in Computational Intelligence
Publication statusPublished - 2015


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