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Open Access

High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan 6516738695, Iran
Department of Energy Engineering, Zarqa University, Zarqa 13132, Jordan
Department of Informatics, University of Oslo, Oslo 0316, Norway
Department of Computer Science, Malmö University, Malmö 20506, Sweden
Shandong Provincial University Laboratory for Protected Horticulture, Weifang University of Science and Technology, Weifang 261100, China
Department of Electrical and Electronics Engineering, Nişantaşı University, Istanbul 34481742, Türkiye
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Abstract

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

Keywords

medical dataMessage Passing Interface (MPI)OpenMPCompute Unified Device Architecture (CUDA)packet classificationtuple space algorithmGraphics Processing Unit (GPU) cluster

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Tsinghua Science and Technology
Volume 29 Issue 4,
August 2024
Pages 1118-1137
DOI: 10.26599/TST.2023.9010088
Cite this article:
Fazel-Najafabadi A, Abbasi M, Attar HH, et al. High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments. Tsinghua Science and Technology, 2024, 29(4): 1118-1137. https://doi.org/10.26599/TST.2023.9010088

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Received: 29 May 2023
Revised: 18 July 2023
Accepted: 06 August 2023
Published: 09 February 2024
© The Author(s) 2024.

The articles published in this open access journal are distributed under the terms of theCreative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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