Hardware Accelerated Alignment Algorithm for Optical Labeled Genomes

Pingfan Meng, Matthew Jacobsen, Motoki Kimura, Vladimir Dergachev, Thomas Anantharaman, Michael Requa, Ryan Kastner
2016 ACM Transactions on Reconfigurable Technology and Systems  
De novo assembly is a widely used methodology in bioinformatics. However, the conventional short-read based de novo assembly is incapable of reliably reconstructing the large-scale structures of human genomes. Recently, a novel optical label based technology has enabled reliable large-scale de novo assembly. Despite its advantage in large-scale genome analysis, this new technology requires a more computationally intensive alignment algorithm than its conventional counterpart. For example, the
more » ... n-time of reconstructing a human genome is on the order of 10, 000 hours on a sequential CPU. Therefore, in order to practically apply this new technology in genome research, accelerated approaches are desirable. In this article, we present three different accelerated approaches, multi-core CPU, GPU and FPGA. Against the sequential software baseline, our multi-core CPU design achieved a 8.4× speedup while the GPU and FPGA designs achieved 13.6× and 115× speedups respectively. We also discuss the details of the design space exploration of this new assembly algorithm on these three different devices. Finally, we compare these devices in performance, optimization techniques, prices and design efforts.
doi:10.1145/2840811 fatcat:i4gucx63unafrmd6x5urd46d6y