ReGen: Optimizing Genetic Selection Algorithms for Heterogeneous Computing

<p>GenSel is a genetic selection analysis tool used to determine which genetic markers are informational for a given trait. Performing genetic selection related analyses is a time consuming and computationally expensive task. Due to an expected increase in the number of genotyped individuals, analysis times will increase dramatically. Therefore, optimization efforts must be made to keep analysis times reasonable.</p> <p>This thesis focuses on optimizing one of GenSel’s underlying algorithms for heterogeneous computing. The resulting algorithm exposes task-level parallelism and data-level parallelism present but inaccessible in the original algorithm. The heterogeneous computing solution, ReGen, outperforms the optimized CPU implementation achieving a 1.84 times speedup.</p>

Name thesis:degree_name

MS in Computer Science

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2014

Author dc:creator

• Winkleblack, Scott Kenneth Swinkleb

Contributors dc:contributor

• Chris Lupo

• Heterogeneous computing
• Bayes methods
• Bioinformatics
• Computer and Systems Architecture
• Other Computer Sciences
• Theory and Algorithms

Identifier

10.15368/theses.2014.81

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-2325