Imperial College London
Professor Wayne Luk

ProfessorWayneLuk

Faculty of Engineering, Department of Computing

Professor of Computer Engineering
 
 
 
//

Contact

 

+44 (0)20 7594 8313w.luk Website

 
 
//

Location

 

434Huxley BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Arram:2016:10.1109/FPT.2015.7393126,
author = {Arram, J and Pflanzer, M and Kaplan, T and Luk, W},
doi = {10.1109/FPT.2015.7393126},
publisher = {IEEE},
title = {FPGA acceleration of reference-based compression for genomic data},
url = {http://dx.doi.org/10.1109/FPT.2015.7393126},
year = {2016}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - One of the key challenges facing genomics today is efficiently storing the massive amounts of data generated by next-generation sequencing platforms. Reference-based compression is a popular strategy for reducing the size of genomic data, whereby sequence information is encoded as a mapping to a known reference sequence. Determining the mapping is a computationally intensive problem, and is the bottleneck of most reference-based compression tools currently available. This paper presents the first FPGA acceleration of reference-based compression for genomic data. We develop a new mapping algorithm based on the FM-index search operation which includes optimisations targeting the compression ratio and speed. Our hardware design is implemented on a Maxeler MPC-X2000 node comprising 8 Altera Stratix V FPGAs. When evaluated against compression tools currently available, our tool achieves a superior compression ratio, compression time, and energy consumption for both FASTA and FASTQ formats. For example, our tool achieves a 30% higher compression ratio and is 71.9 times faster than the fastqz tool.
AU  - Arram,J
AU  - Pflanzer,M
AU  - Kaplan,T
AU  - Luk,W
DO  - 10.1109/FPT.2015.7393126
PB  - IEEE
PY  - 2016///
TI  - FPGA acceleration of reference-based compression for genomic data
UR  - http://dx.doi.org/10.1109/FPT.2015.7393126
UR  - http://hdl.handle.net/10044/1/43196
ER  -
Download