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The Research and Optimization of Small High-Performance Linux-Based Cluster

Author: LiZuo
Tutor: XueZhi
School: Shanghai Jiaotong University
Course: Communication and Information System
Keywords: Linux High-performance Computing MPI MatrixMultiplication HPL
CLC: TP316.81
Type: Master's thesis
Year: 2012
Downloads: 130
Quote: 1
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Abstract


The demand of computing power in both commercial and scientificareas is growing rapidly. The development of traditional high-performancearchitecture, like vector-based high-performance computer processors andSMP, is limited in scientific research and some other professional fields.The development of Linux system and network technology provides agood condition for the development of cluster technology. Linux-basedhigh-performance cluster is widely used in many areas because of its goodscalability, good compatibility and low cost and becomes one of the mostimportant objects of study.A Linux-based high-performance cluster is built and it includes manyhardware and software modules such as management node, compute nodes,networking equipments, NFS file sharing system, MPI parallelprogramming library, BLAS etc.A matrix multiplication is parallel programmed in the language ofC+MPI under the high-performance cluster platform. Matrix multiplicationis one of the most widely used functions in the field of science andengineering computing. After running the parallel application withdifferent problem sizes and different number of processors and comparingthe test results, the parallelism of the Linux-based cluster is verified.HPL is the most popular method to measure the floating pointperformance of the high-performance computers, and is also the standardBenchmark for TOP500 super computers. Optimization of HPL is animportant step to improve the performance of high-performance computers.Since the cluster system is complicated and HPL provides a lot ofparameters for the users to tune, there is no general and platform independent method to optimize. The traditional methods are generallyexperience-based and exhaustive. They are time-consuming and areimpossible to cover all the possible combinations. This paper presents amethod based on the sort of impact factors of parameters and find out thebest tuning path of the parameters. A small Linux-based high-performancecluster which contains 8-node, 32 cores clocked at 2.67GHz is optimizedaccording to this method and an efficiency of 66% is obtained.

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