Parallel Motion Estimation Implementation for Different Block Matching Algorithms onto GPGPU
Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
XXVII SIM – South Symposium on Microelectronics, 2012
@article{monteiro2012parallel,
title={PARALLEL MOTION ESTIMATION IMPLEMENTATION FOR DIFFERENT BLOCK MATCHING ALGORITHMS ONTO GPGPU},
author={Monteiro, Eduarda and Maule, Marilena and Sampaio, Felipe and Diniz, Cl{‘a}udio and Zatt, Bruno and Bampi, Sergio},
year={2012}
}
This work presents an efficient method to map Motion Estimation (ME) algorithms onto General Purpose Graphic Processing Unit (GPGPU) architectures using CUDA programming model. Our method jointly exploits the massive parallelism available in current GPGPU devices and the parallelization potential of ME algorithms: Full Search (FS) and Diamond Search (DS). Our main goal is to evaluate the feasibility of achieving real-time high-definition video encoding performance running on GPUs. For comparison reasons, multi-core parallel and distributed versions of these algorithms were developed using OpenMP and MPI (Message Passing Interface) libraries, respectively. The CUDA-based solutions achieve the highest speed-up in comparison with OpenMP and MPI versions for both algorithms and, when compared to the state-of-the-art, our FS and DS solutions reach up to 18x and 11x speed-up, respectively.
September 17, 2013 by hgpu
