Delivering Faster Results Through Parallelisation and GPU Acceleration

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.