University of Illinois Urbana-Champaign

Efficient parallelization of Bowtie 2 with OpenCL on GPU

Yan, Yan

Content Files
YAN-THESIS-2016.pdf

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https://hdl.handle.net/2142/92977

Description

Title
Efficient parallelization of Bowtie 2 with OpenCL on GPU
Author(s)
Yan, Yan
Issue Date
2016-07-21
Director of Research (if dissertation) or Advisor (if thesis)
Chen, Deming
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2016-11-10T18:35:35Z
Keyword(s)
  • OpenCL
  • Bowtie 2
  • Sequence Aligner
  • Smith-Waterman
Abstract
As a crucial and computation-intensive aspect in bioinformatics, sequence alignment has gained considerable attention from researchers and developers. Among all the sequence aligners, Bowtie 2 is one of the most commonly used, due to its high speed and accuracy. This thesis presents a parallel implementation of Bowtie 2 with OpenCL, which is a parallel programming model that is becoming widely known and receiving great interest from researchers in recent years. This OpenCL implementation has high portability on various devices, such as multi-core CPU, GPU, and FPGA. This thesis focuses on an efficient and accurate parallelization on GPU. Optimizations that can be accommodated to any devices have been applied, as well as GPU-related optimizations.
Graduation Semester
2016-08
Type of Resource
text
Permalink
http://hdl.handle.net/2142/92977
Copyright and License Information
Copyright 2016 Yan Yan

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Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois