Gigabyte-scale alignment acceleration of biological sequences via Ethernet streaming

Abstract

We describe the design of a PC-to-FPGA data streaming platform that enables hardware acceleration of gigabyte scale input data. Specifically, the acceleration is an FPGA implementation of the Dialign Algorithm, which performs both global and local alignment of query biological sequences against relatively larger reference strands of biological sequences. Earlier implementations of this algorithm could not be scaled to handle gigabyte-length reference sequences, nor megabyte-length query sequences, due to the inherent limitations of available memory and logic on single-FPGA platforms. We solve these issues via the design of an Ethernet channel to stream the reference sequence, and describe the novel use of SATA based Solid State Drives (SSDs) to time multiplex the FPGA logic into handling larger query sequences as well. In doing so, this paper also presents a general method to achieve gigabyte-depth FIFOs on commercially available FPGA development boards. This benefits data-intensive acceleration even outside of the bioinformatics application domain. Through the development of our acceleration logic and careful coupling of the required IO peripherals, we have successfully demonstrated a processing time of 28.61 minutes for a 200 base-pair query-sequence aligned against a 1 GB reference-sequence, a rate that is limited only by SATA 2 SDD write speeds. The present runtime offers a 38× speedup (18.36 hours down to 28.61 minutes) compared to standalone PC based processing.