Optimizations in Bioinformatics using GPU Processing on Binary Data
School of Computer Science, Carleton University, Ottawa, Canada
Carleton University, 2012
@article{belmadani2012optimizations,
title={Optimizations in Bioinformatics using GPU Processing on Binary Data},
author={Belmadani, M.},
year={2012}
}
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.
January 8, 2013 by hgpu
