Genetically improved BarraCUDA

• Main Authors: W. B. Langdon, Brian Yee Hong Lam
• Format: Article
• Language: English
• Published: BMC 2017-08-01
• Series: BioData Mining
• Subjects: GPGPU; Parallel computing; Genetic improvement; Double-ended DNA sequence; Nextgen NGS
• Online Access: http://link.springer.com/article/10.1186/s13040-017-0149-1

Abstract Background BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised using “Genetic Improvement”. Results The genetically improved (GI) code is up to three times faster on short paired end reads from The 1000 Genomes Project and 60% more accurate on a short BioPlanet.com GCAT alignment benchmark. GPGPU BarraCUDA running on a single K80 Tesla GPU can align short paired end nextGen sequences up to ten times faster than bwa on a 12 core server. Conclusions The speed up was such that the GI version was adopted and has been regularly downloaded from SourceForge for more than 12 months.