本文選題：SMP機(jī)群 + MPI+OpenMP��； 參考：《曲阜師范大學(xué)》2014年碩士論文

【摘要】：隨著科學(xué)技術(shù)的不斷發(fā)展，各個領(lǐng)域?qū)τ诖笠?guī)模數(shù)據(jù)處理的需求日益增長，這極大的促進(jìn)了并行計算的發(fā)展，同時高性能計算機(jī)也因此越來越受到廣泛的應(yīng)用，其中SMP機(jī)群因為具有較高的性價比和良好的可擴(kuò)展性以及可用性等特點(diǎn)備受歡迎，成為當(dāng)前并行計算機(jī)領(lǐng)域中的主流結(jié)構(gòu)，也成為了高性能計算領(lǐng)域的研究重點(diǎn)。本文的主要研究內(nèi)容就是SMP機(jī)群以及適用于該體系結(jié)構(gòu)的編程模型，并提出了優(yōu)化措施。 本文首先介紹了課題的研究背景以及并行計算技術(shù)和并行計算機(jī)體系結(jié)構(gòu)的發(fā)展。隨后介紹了幾種當(dāng)代流行的并行計算機(jī)系統(tǒng)，，對其結(jié)構(gòu)和特點(diǎn)進(jìn)行了詳細(xì)分析，同時對當(dāng)前主流的并行編程模型進(jìn)行了介紹。接著對本文的重點(diǎn)進(jìn)行了詳細(xì)研究和分析：SMP機(jī)群及適用于SMP機(jī)群的并行編程模型。論文中對SMP機(jī)群的體系結(jié)構(gòu)做了詳細(xì)分析，SMP機(jī)群結(jié)合了SMP系統(tǒng)和機(jī)群系統(tǒng)的優(yōu)點(diǎn)，它以SMP作為節(jié)點(diǎn)，內(nèi)部采用共享存儲的結(jié)構(gòu)，而節(jié)點(diǎn)之間則采用分布存儲的結(jié)構(gòu)，在SMP機(jī)群上可以充分利用共享存儲編程模型和分布存儲編程模型進(jìn)行編程。其中OpenMP和MPI作為兩種編程模型的代表同樣是本文的研究重點(diǎn)，針對SMP機(jī)群特殊的體系結(jié)構(gòu)，介紹了一種MPI+OpenMP的混合編程模型，并給出了混合編程模型的結(jié)構(gòu)、實現(xiàn)機(jī)制以及其優(yōu)勢，分析了MPI+粗粒度OpenMP和MPI+細(xì)粒度OpenMP的兩種并行化方式的優(yōu)缺點(diǎn)，同時提出了一些優(yōu)化措施，進(jìn)一步提高混合編程模型的性能。 本文的實驗部分首先介紹了實驗的軟硬件環(huán)境，然后介紹了實驗部分進(jìn)行性能評測的方法，實驗重點(diǎn)是實現(xiàn)了N體問題的PP算法的并行程序設(shè)計。針對這個問題設(shè)計了相應(yīng)的MPI程序和MPI+OpenMP混合程序，并對混合編程進(jìn)行了優(yōu)化，最后將程序在曙光TC5000機(jī)群上對程序進(jìn)行了測試。通過測試獲得程序的執(zhí)行時間進(jìn)而求得加速比，證明了在一定情況下混合編程模型是可以通過優(yōu)化進(jìn)一步提高性能的，對比分析得出在SMP機(jī)群上MPI+OpenMP混合編程模型要好于純MPI編程模型。論文的最后對前面的主要研究內(nèi)容進(jìn)行了概括，并對下一步可進(jìn)行的工作進(jìn)行了展望。
[Abstract]:With the continuous development of science and technology, the demand for large-scale data processing in various fields is increasing, which greatly promotes the development of parallel computing, at the same time, high-performance computers are more and more widely used. Among them, SMP cluster is popular because of its high performance-price ratio, good scalability and usability. It has become the mainstream structure in the field of parallel computing, and has also become the focus of research in the field of high performance computing. The main research content of this paper is SMP cluster and programming model suitable for this architecture, and the optimization measures are proposed. This paper first introduces the research background and the development of parallel computing technology and parallel computer architecture. Then several popular parallel computer systems are introduced, their structure and characteristics are analyzed in detail, and the current mainstream parallel programming models are introduced. Then, the emphasis of this paper is studied and analyzed in detail, and the parallel programming model for SMP cluster is analyzed. In this paper, the architecture of SMP cluster is analyzed in detail, which combines the advantages of SMP system and cluster system. It takes SMP as the node, adopts the structure of shared storage, and adopts the structure of distributed storage among nodes. The shared storage programming model and the distributed storage programming model can be fully utilized in the SMP cluster. OpenMP and MPI as representatives of two programming models are also the focus of this paper. According to the special architecture of SMP cluster, a hybrid programming model of MPI OpenMP is introduced, and the structure of hybrid programming model is given. The implementation mechanism and its advantages are analyzed. The advantages and disadvantages of the two parallelization methods of MPI coarse-grained OpenMP and MPI fine-grained OpenMP are analyzed. At the same time, some optimization measures are proposed to further improve the performance of the hybrid programming model. In the experiment part, we first introduce the hardware and software environment of the experiment, and then introduce the method of performance evaluation in the experiment part. The key point of the experiment is to realize the parallel programming of PP algorithm for N-body problem. In order to solve this problem, the corresponding MPI program and MPI OpenMP hybrid program are designed and optimized. Finally, the program is tested on the dawning TC5000 cluster. The speedup ratio is obtained by testing the execution time of the program. It is proved that the hybrid programming model can further improve the performance through optimization under certain circumstances. Comparison and analysis show that MPI OpenMP hybrid programming model is better than pure MPI programming model on SMP cluster. At the end of the paper, the main research contents are summarized, and the future work is prospected.
【學(xué)位授予單位】：曲阜師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP311.11;TP338.6

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