Publication detail

Multi-GPU Implementation of k-Nearest Neighbor Algorithm

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

Original Title

Multi-GPU Implementation of k-Nearest Neighbor Algorithm

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

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

RIV year

2014

Released

9. 7. 2015

Location

Berlin, Germany

ISBN

978-1-4799-8497-8

Book

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

Pages from

764

Pages to

767

Pages count

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"
}