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MAŠEK, J.; BURGET, R.; KARÁSEK, J.; UHER, V.; DUTTA, M.
Original Title
Multi-GPU Implementation of k-Nearest Neighbor Algorithm
English Title
Type
Paper in proceedings (conference paper)
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.
English abstract
Keywords
Artificial intelligence, big data, GPU, high performance computing, k-NN, multi–GPU, OpenCL.
Key words in English
Authors
RIV year
2015
Released
09.07.2015
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" }