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University of Illinois at Urbana-Champaign

FPGA acceleration of short read alignment with high-level synthesis

Abstract

dc:description

With the introduction of next-generation sequencing (NGS) technologies, DNA sequencing is becoming an increasingly widespread process. When performed on human patients, it can allow for the prediction and prevention of diseases. An essential part of this bioinformatics pipeline is short read alignment}, which refers to aligning short fragments of DNA to the large and expansive reference genome. This can be a very time-consuming process with much room for improvement. This thesis improves on Bowtie 2, an aligner that is already very popular and high-performing. Through the use of OpenCL, it is possible to parallelize this application for both GPU and FPGA by using the same code. Several different levels of parallelism are implemented in order to achieve speedup on Bowtie 2.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chen, Daniel E
Contributors dc:contributor
  • Chen, Deming

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • Copyright 2017 Daniel E. Chen
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/97641
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/97641

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Chen, Daniel E. FPGA acceleration of short read alignment with high-level synthesis. Thesis thesis, University of Illinois at Urbana-Champaign, 2017. http://hdl.handle.net/2142/97641