Title :
GPU-accelerated dynamic functional connectivity analysis for functional MRI data using OpenCL
Author :
Akgun, Devrim ; Sakoglu, Unal ; Mete, Mutlu ; Esquivel, Johnny ; Adinoff, Bryon
Author_Institution :
Comput. Eng. Dept. of Technol. Fac., Sakarya Univ., Sakarya, Turkey
Abstract :
Intense computations in engineering and science, especially bioinformatics have been made practical by the recent advances in Graphical Processing Unit (GPU) computing technology. In this study, implementation and performance evaluations for a GPU-accelerated dynamic functional connectivity (DFC) analysis, which is an analysis method for investigating dynamic interactions among different brain networks, is presented. Open Computing Library (OpenCL), which provides a general framework for GPU computing, is utilized, and it is shown to reduce the DFC analysis computation time. The parallel implementation with OpenCL provides up to 10x speed-up over sequential implementation.
Keywords :
bioinformatics; biomedical MRI; graphics processing units; performance evaluation; public domain software; GPU computing technology; GPU-accelerated DFC analysis; GPU-accelerated dynamic functional connectivity analysis; OpenCL; bioinformatics; functional MRI data; graphical processing unit computing technology; open computing library; Acceleration; Algorithm design and analysis; Correlation; Graphics processing units; Magnetic resonance imaging; Neurofeedback; Real-time systems;
Conference_Titel :
Electro/Information Technology (EIT), 2014 IEEE International Conference on
Conference_Location :
Milwaukee, WI
DOI :
10.1109/EIT.2014.6871811
