GPU acceleration of advanced K-mer counting for computational genomics

k-mer counting is a popular pre-processing step in many bioinformatic algorithms. KMC2 is one of the most popular tools for k-mer counting. In this work, we leverage the computational power of the GPU to accelerate KMC2. Our goal is to reduce the overall runtime of many genome analysis tasks that use k-mer counting as an essential step. We achieved 4.03x speedup using one GTX 1080 Ti with one CPU (Xeon E5-2603) thread and 5.88x speedup using one GPU with four CPU threads over KMC2 running on a single CPU thread. This speedup is significant because accelerating k-mer counting is challenging due to reasons like serialized portions of code and overhead of disk operations.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Li, Huiren

Contributors dc:contributor

• Chen, Deming

• k-mer counting
• GPU acceleration

Statement dc:rights

• Copyright 2018 Huiren Li

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/101639

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/101639