The sequencing capability of Next Generation Sequencing platforms continues to increase, but mapping short DNA fragments to large genomic sequences still constitutes a challenge in many bioinformatic applications. In this paper, we present BWaveR, a heterogeneous system leveraging FPGAs to increase the execution efficiency of the sequence matching process, based on succinct data structures that allow to encode large sequences in a minimal memory footprint, while still granting fast queries on them. Our design, evaluated on a Xilinx Alveo U200, results up to 4.9x faster and 26x more power-efficient than Bowtie2, a state-of-the-art equivalent software, run with 16threads, without any loss in accuracy.

Leveraging succinct data structures for DNA sequence mapping on FPGA

Di Donato G. W.;Zeni A.;Di Tucci L.;Santambrogio M. D.
2020-01-01

Abstract

The sequencing capability of Next Generation Sequencing platforms continues to increase, but mapping short DNA fragments to large genomic sequences still constitutes a challenge in many bioinformatic applications. In this paper, we present BWaveR, a heterogeneous system leveraging FPGAs to increase the execution efficiency of the sequence matching process, based on succinct data structures that allow to encode large sequences in a minimal memory footprint, while still granting fast queries on them. Our design, evaluated on a Xilinx Alveo U200, results up to 4.9x faster and 26x more power-efficient than Bowtie2, a state-of-the-art equivalent software, run with 16threads, without any loss in accuracy.
2020
Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020
978-1-7281-7445-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1169864
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