Acceleration of Short Read Alignment with Runtime Reconfiguration

Abstract

Recent advancements in the throughput of nextgeneration sequencing machines pose a huge computational challenge in analyzing the massive quantities of sequenced data produced. A critical initial step of genomic data analysis is short read alignment, which is a bottleneck in the analysis workflow. This paper explores the use of a reconfigurable architecture to accelerate this process, based on the seed-and-extend model of Bowtie2. In the proposed approach, complete information available in sequencing data is integrated into an FPGA alignment pipeline for biologically accurate runtime acceleration. Experimental results show that our architecture achieves a similar alignment rate compared to Bowtie2, mapping reads around twice as fast. Particularly, the alignment time is reduced from 50 minutes to 26 minutes when processing 300M reads.

An FPGA Accelerator of the Wavefront Algorithm for Genomics Pairwise Alignment

“…As a result, some surveys [65]- [67] have been published summarizing the many contributions done over the years. In addition, many production-ready bioinformatics tools already incorporate custom FPGA accelerators [35]- [38], [45], [52], [53].…”

“…Nevertheless, these solutions lack the flexibility to meet the requirements of many biological applications. For this reason, FPGA accelerators that fully implement the gap-affine model (i.e., the SWG algorithm) are usually preferred [14], [15], [32]- [35], [53]- [64].…”