Performance Improvement of Data Mining in Weka through GPU Acceleration

Engel Tiago Augusto 1 Andrea Schwertner Charão 1 Manuele Kirsch Pinheiro 2 Luiz Angelo Steffenel 3
1 LSC - Laboratório de Sistemas de Computação
2 CRI - Centre de Recherche en Informatique de Paris 1
3 CRESTIC - Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804
Abstract : Data mining tools may be computationally demanding, so there is an increasing interest on parallel computing strategies to improve their performance. The popularization of Graphics Processing Units (GPUs) increased the computing power of current desktop computers, but desktop-based data mining tools do not usually take full advantage of these architectures. This paper exploits an approach to improve the performance of Weka, a popular data mining tool, through parallelization on GPU-accelerated machines. From the profiling of Weka object-oriented code, we chose to parallelize a matrix multiplication method using state-of-the-art tools. The implementation was merged into Weka so that we could analyze the impact of parallel execution on its performance. The results show a significant speedup on the target parallel architectures, compared to the original, sequential Weka code.
Mots-clés : data mining tools parallel computing GPU
Type de document :
Communication dans un congrès
The 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), the 4th International Conference on Sustainable Energy Information Technology (SEIT-2014), Jun 2014, Hasselt, Belgium. Elsevier, 32, pp.93 - 100, 2014, 〈10.1016/j.procs.2014.05.402〉
Liste complète des métadonnées
https://hal-paris1.archives-ouvertes.fr/hal-01003008
Contributeur : Manuele Kirsch Pinheiro <>
Soumis le : dimanche 8 juin 2014 - 19:45:01
Dernière modification le : mercredi 14 février 2018 - 16:54:01

Lien texte intégral

openaccess

Identifiants

Collections

UNIV-PARIS1 | CRI | URCA | CRESTIC

Citation

Engel Tiago Augusto, Andrea Schwertner Charão, Manuele Kirsch Pinheiro, Luiz Angelo Steffenel. Performance Improvement of Data Mining in Weka through GPU Acceleration. The 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), the 4th International Conference on Sustainable Energy Information Technology (SEIT-2014), Jun 2014, Hasselt, Belgium. Elsevier, 32, pp.93 - 100, 2014, 〈10.1016/j.procs.2014.05.402〉. 〈hal-01003008〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

205

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD