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MAŠEK, J. BURGET, R. POVODA, L. DUTTA, M.
Original Title
Multi–GPU Implementation of Machine Learning Algorithm using CUDA and OpenCL
Type
journal article - other
Language
English
Original Abstract
Using modern Graphic Processing Units (GPUs) becomes very useful for computing complex and time consuming processes. GPUs provide high–performance computation capabilities with a good price. This paper deals with a multi–GPU OpenCL and CUDA implementations of k–Nearest Neighbor (k– NN) algorithm. This work compares performances of OpenCL and CUDA implementations where each of them is suitable for different number of used attributes. The proposed CUDA algorithm achieves acceleration up to 880x 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, comparison, CUDA, GPU, high performance computing, k-NN, multi–GPU, OpenCL.
Authors
MAŠEK, J.; BURGET, R.; POVODA, L.; DUTTA, M.
Released
10. 6. 2016
Publisher
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems
ISBN
1805-5443
Periodical
Year of study
5
Number
2
State
Czech Republic
Pages from
101
Pages to
107
Pages count
7
URL
http://ijates.org/index.php/ijates/article/view/142
BibTex
@article{BUT125826, author="Jan {Mašek} and Radim {Burget} and Lukáš {Povoda} and Malay Kishore {Dutta}", title="Multi–GPU Implementation of Machine Learning Algorithm using CUDA and OpenCL", journal="International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems", year="2016", volume="5", number="2", pages="101--107", doi="10.11601/ijates.v5i2.142", issn="1805-5443", url="http://ijates.org/index.php/ijates/article/view/142" }