IMPLEMENTATION OF MOTION ESTIMATION BASED ON HETEROGENEOUS PARALLEL COMPUTING SYSTEM WITH OPENC - Université de Rennes Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

IMPLEMENTATION OF MOTION ESTIMATION BASED ON HETEROGENEOUS PARALLEL COMPUTING SYSTEM WITH OPENC

Résumé

Heterogeneous computing system increases the performance of parallel computing in many domain of general purpose computing with CPU, GPU and other accelerators. Open Computing Language (OpenCL) is the first open, royaltyfree standard for heterogenous computing on multi hardware platforms. In this paper, we propose a parallel Motion Estimation (ME) algorithm implemented using OpenCL and present several optimization strategies applied in our OpenCL implementation of the motion estimation. In the same time, we implement the proposed algorithm on our heterogeneous computing system which contains one CPU and one GPU, and propose one method to determine the balance to distribute the workload in heterogeneous computing system with OpenCL. According to experiments, our motion estimator with achieves 100 to 150 speed-up compared with its implementation with C code executed by single CPU core and our proposed method obtains obviously enhancement of performance in based on our heterogeneous computing system.
Fichier principal
Vignette du fichier
2012_HPCC_Jinglin.pdf (559.38 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00763860 , version 1 (11-12-2012)

Identifiants

  • HAL Id : hal-00763860 , version 1

Citer

Jinglin Zhang, Jean François Nezan, Jean-Gabriel Cousin. IMPLEMENTATION OF MOTION ESTIMATION BASED ON HETEROGENEOUS PARALLEL COMPUTING SYSTEM WITH OPENC. 14th IEEE International Conference on High Performance Computing and Communications (HPCC), Jun 2012, Liverpool, United Kingdom. pp.NC. ⟨hal-00763860⟩
189 Consultations
1269 Téléchargements

Partager

Gmail Facebook X LinkedIn More