Optimizations in Bioinformatics using GPU Processing on Binary Data

Manuel Belmadani
School of Computer Science, Carleton University, Ottawa, Canada
Carleton University, 2012


   title={Optimizations in Bioinformatics using GPU Processing on Binary Data},

   author={Belmadani, M.},



Source Source   



This experiment explores the performance of GPUs in genetic algorithms using binary data. The experiment executes a genetic algorithm which works with binary sequences that are processed on the GPU. The hypothesis is that an optimal number of maximum threads (likely larger than small) is required to have an optiomal runtime. The results show that a maximum number of threads of 128 generally performs better than other sizes, notably 256, 64,32 etc. Some exceptions are also shown, possibly due to the differents natures of the kernels. This study is of interest the field of bioinformatics and parallel programming, as knowledge of the latter can reduce the runtime for tasks in the former.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Contact us: