FPGA-based accelerator for adaptive banded event alignment in nanopore sequencing data analysis.

Abstract

Background: Adaptive Banded Event Alignment (ABEA) stands as a critical algorithmic component in sequence polishing and DNA methylation detection, employing dynamic programming to align raw Nanopore signal with reference reads. Motivated by the observation that, compared to CPUs and GPUs, cutting-edge FPGAs demonstrate-in certain cases-superior performance at a reduced cost and energy consumption, this paper presents an efficient FPGA-based accelerator for ABEA, leveraging the inherent high parallelism and sequential access pattern within ABEA.

Result: Our proposed FPGA-based ABEA accelerator significantly enhances ABEA performance compared to the original CPU-based implementation in Nanopolish as well as the state-of-art acceleration on GPU and FPGA platforms. Specifically, targeting Xilinx VU9P, our accelerator achieves an average throughput speedup of 10.05 $\times$ over the CPU-only implementation, an average 1.81 $\times$ speedup over the state-of-art GPU acceleration with only 7.2% of the energy, and a speedup of 10.11 $\times$ compared to an existing FPGA accelerator.

Conclusion: Our work demonstrates that intensive genome analysis can benefit significantly from cutting-edge FPGAs, offering improvements in both performance and energy consumption.