Detail publikace

Multi-GPU Implementation of k-Nearest Neighbor Algorithm

MAŠEK, J. BURGET, R. KARÁSEK, J. UHER, V. DUTTA, M.

Originální název

Multi-GPU Implementation of k-Nearest Neighbor Algorithm

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Using modern Graphic Processing Units (Gills) becomes very useful for computing complex and time consuming processes. CPUs provide high performance computation capabilities with a good price. This paper deals with a multi-GPU OpenCL implementation of k-Nearest Neighbor (k-NN) algorithm. The proposed OpenCL algorithm achieves acceleration up to 750x in comparison with a single thread CPU version. The common k-NN was modified to be faster when the lower number of k neighbors is set. The performance of algorithm was verified with two GPUs dual-core NVIDIA GeForce GTX 690 and CPU Intel Core i7 3770 with 4.1 GHz frequency. The results of speed up were measured for one GPU, two GPUs, three and four GPUs. We performed several tests with data sets containing up to 4 million elements with various number of attributes.

Klíčová slova

Artificial intelligence, big data, GPU, high performance computing, k-NN, multi–GPU, OpenCL.

Autoři

MAŠEK, J.; BURGET, R.; KARÁSEK, J.; UHER, V.; DUTTA, M.

Rok RIV

2014

Vydáno

9. 7. 2015

Místo

Berlin, Germany

ISBN

978-1-4799-8497-8

Kniha

Proceedings of the 38th International Conference on Telecommunication and Signal Processing

Strany od

764

Strany do

767

Strany počet

4

URL

https://ieeexplore.ieee.org/document/7296368

BibTex

@inproceedings{BUT107205,
  author="Jan {Mašek} and Radim {Burget} and Jan {Karásek} and Václav {Uher} and Malay Kishore {Dutta}",
  title="Multi-GPU Implementation of k-Nearest Neighbor Algorithm",
  booktitle="Proceedings of the 38th International Conference on Telecommunication and Signal Processing",
  year="2015",
  pages="764--767",
  address="Berlin, Germany",
  doi="10.1109/TSP.2015.7296368",
  isbn="978-1-4799-8497-8",
  url="https://ieeexplore.ieee.org/document/7296368"
}