GPU cluster for accelerated processing and visualisation of scientific and engineering data

Matthew Newall, Violeta Holmes, Paul Lunn

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The ability to process, visualise, and work with large volumes of data in a way that is fast, meaningful, and accurate is an essential part of many fields of scientific research today. The success of video game industry has resulted in ongoing developments in the complexity of Graphical Processing Units (GPU), as well as rapidly falling cost per core. Their characteristics make them excellently suited to any task exhibiting a high level of data parallelism. Recent development of GPU architectures is aimed at HPC systems and applications. In this paper we are presenting our experience in designing and deploying a small dedicated GPU based cluster for processing and visualising data generated by engineering and scientific application. This GPU cluster is helping our researchers to analyse complex data using visualisation, and to accelerate large data processing. We have shown that our GPU cluster solution can achieve five to ten times speed up compared to the CPU system. As a result of our work we can demonstrate that even a small GPU cluster can benefit Higher Education institutions.

Original languageEnglish
Title of host publicationProceedings of 2014 Science and Information Conference, SAI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9780989319317
Publication statusPublished - 7 Oct 2014
Event2014 Science and Information Conference - Park Inn by Radisson Hotel, London, United Kingdom
Duration: 27 Aug 201429 Aug 2014 (Link to Conference Details )


Conference2014 Science and Information Conference
Abbreviated titleSAI 2014
Country/TerritoryUnited Kingdom
Internet address


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