Accelerating Phylogeny-Aware Short DNA Read Alignment with FPGAs

Abstract

Abstract-Recent advances in molecular sequencing technology have given rise to novel algorithms for simultaneously aligning short sequence reads to reference sequence alignments and corresponding evolutionary reference trees. We present a complete hardware/software implementation for the acceleration of a program called PaPaRa, a newly introduced dynamic programming algorithm for this purpose.We verify the correctness of the proposed architecture on a real FPGA and introduce a straight-forward communication protocol (using gigabit ethernet) for seamless integration with the encapsulating steering software that is executed on a PC processor. The hardware description and the software implementation are freely available for download.When mapped to a Virtex 6 FPGA, our reconfigurable architecture can compute 133.4 billion cell updates per second for the novel, tree-based alignment kernel of PaPaRa. Compared to PaPaRa, running on a 3.2GHz Intel Core i5 CPU, we obtain speedups for the alignment kernel, that range between 170 and 471. For the entire application, that is, the alignment kernel and the trace-back step, we obtain speedups between 74 and 118.

FPGASW: Accelerating Large-Scale Smith–Waterman Sequence Alignment Application with Backtracking on FPGA Linear Systolic Array

“…As a result, a larger linear PE array can be fitted in a single device. Thus, the theoretical peak performance (equals array size × clock frequency × the number of score processing units) achieved in paper [31] and [33] is slightly higher than our implementations. …”

“…(2) Compared to other hardware SW implementations without backtracking, our comprehensive computing performance is also superior to others obviously. It should be explained that [31] and [33] integrated several small-scaled Score Processing Units for multiple DNA Short-Read Mapping tasks in parallel on a single FPGA chip. First, no data dependency exists among multiple coarse-grained tasks for short-read mapping.…”

“…In recent years, there are several new studies [31][32][33][34][35][36] that focus on short sequence alignment on new generation Virtex-5 or Virtex-6 FPGA-based system. Those literatures only consider the hardware implementation for scoring stage in the SW algorithm (without backtracking) and only support short DNA read mapping less than 512 base pairs, except for the last one [36], which implemented the longer read alignment with the length up to 4096 base pairs.…”

Reconfigurable Computing Architectures

“…These short-read sequences are aligned against a reference DNA sequence to get the best (and fastest) alignment and to identify potential mutations (additions, deletions and/or substitutions of base-pairs) in the target DNA being analyzed. A combination of software and reconfigurable hardware was used to achieve a two order of magnitude speedup over a software-only solution [237]. Subsequent work [238] tackled the problem of matching millions of short read sequences against a reference DNA sequence through the hardware-based acceleration of the popular BLAT-like Fast Accurate Search algorithm (BFAST) software algorithm.…”

Design and analysis of bioinformatics algorithms on an FPGA platform

“…An FPGA-based system is designed in [4] to align the query sequence to an ancestral state vector. The kernel algorithm is a parsimony-based phylogeny-aware short read alignment (PaPaRa) [14], which is similar to a dynamic programming algorithm but designed for evolutionary tree analysis.…”