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

作　　者：Azam Fazel-Najafabadi Mahdi Abbasi Hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman 

机构地区：[1]Department of Computer Engineering,Faculty of Engineering,Bu-Ali Sina University,Hamedan 6516738695,Iran [2]Department of Energy Engineering,Zarqa University,Zarqa 13132,Jordan [3]Department of Informatics,University of Oslo,Oslo 0316,Norway [4]Department of Computer Science,MalmöUniversity,Malmö20506,Sweden [5]Shandong Provincial University Laboratory for Protected Horticulture,Weifang University of Science and Technology,Weifang 261100,China [6]Department of Electrical and Electronics Engineering,NişantaşıUniversity,Istanbul 34481742,Türkiye

出　　处：《Tsinghua Science and Technology》2024年第4期1118-1137,共20页清华大学学报自然科学版（英文版）

摘　　要：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.

关 键 词：OPENMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster 

分 类 号：U491[交通运输工程—交通运输规划与管理] TP18[交通运输工程—道路与铁道工程]