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.
|Title of host publication||Intelligent Systems in Science and Information 2014|
|Editors||Kohei Arai, Supriya Kapoor, Rahul Bhatia|
|Place of Publication||Switzerland|
|Number of pages||12|
|Publication status||Published - 14 Feb 2015|
|Name||Studies in Computational Intelligence|
- GPU cluster