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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/72121

    Title: 針對長時運算財務分析模型的分散式運算模式效率之比較;Performance Comparison for Distributed Computing Model in Long-Running Financial Analysis Computation
    Authors: 何峻昇;HE,JYUN SHENG
    Contributors: 資訊管理學系
    Keywords: 分散式運算;Hadoop;SAS;MATLAB;JAVA RMI;Distributed Computing, Hadoop, SAS, MATLAB, JAVA RMI
    Date: 2016-07-14
    Issue Date: 2016-10-13 14:27:07 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 目前在全球金融領域中,有許多利用現有財務分析模型做為應用的研究,但存在著一些技術性問題,例如:計算複雜的財務分析模型與處理大數據,需要耗費大量的運算時間。由於目前針對CPU Intensive和I/O Intensive問題,做分散式運算的文獻,沒有公平的標準與開發流程,使得開發者無法得知哪種分散式運算,適合解決什麼樣類型的Intensive特性,以及如何透過成本較低的方式,進行分散式運算。
    本研究針對金融領域所面臨的CPU Intensive和I/O Intensive問題,運用分散式運算模式,提升財務分析模型與大數據在運算上的效率,進而解決大量的運算時間,以及比較三種常用的分散式運算模式,在CPU Intensive和I/O Intensive特性上運算的效率,讓開發者針對特性選擇較適合的分散式運算模式撰寫,來達到提升財務模型在運算上的效率,但結果與原預期效果不合,因此探討如何修正初步流程,讓修正後的流程可以更快找出效率不佳的原因。
    本研究提出修正後初步流程,確實能夠更快找出效率不佳的原因。修正後的流程主要分為七個階段,首先第一步、根據CPU Intensive與I/O Intensive特性,挑選出適合的財務分析模型,之後第二步、決定出適合開發大量複雜運算的程式語言,本研究是採用SAS、MATLAB程式語言開發,第三步、複雜運算的初步效率驗證,針對需要轉換的程式,進行初步效率比較,第四步、為了規範模型程式碼的一制性,因此需要確保程式複雜性,在沒有增加的情況下,將SAS程式轉換成MATLAB程式,第五步、開始撰寫分散式運算程式,讓程式及資料可以達到分散式運算的效果,第六步、進行實測,最後第七步、分析與討論分散式運算模式的效率。;Currently the global financial field, there are many studies about using existed financial analysis model as applications, but there are some technical problems. For example: to calculate complex financial analysis models and handle big data takes lots of computing time. for the current CPU Intensive and I/O Intensive problem, research distributed computing literature no fairer standard and development processes, to make the developers can’t know what kind of distributed computing for solving Intensive what type of properties, and how to through a cost-effective manner to distributed computing.
    In this study, for the financial field faced CPU Intensive and I / O Intensive problem, using distributed computing model to enhance the financial analysis model and big data on the efficiency of operation, thereby solve lot of computing time, and comparison of three common distributed computing model, in the CPU Intensive and I/O Intensive characteristic operation efficiency, to make developers can choose more suitable for the characteristics of the distributed computing model development, enhance the efficiency of financial models in operation, but the result is not the same as the original expected results, research how to amend the original process to quickly identify the cause of inefficiency.
    The study presents a revised preliminary process can really quickly identify poor efficiency reasons. It divided into seven phases, the first step, according to CPU Intensive and I / O Intensive properties, selected more suitable for financial calculation model, the second step, to determine the programming language more suited to the development of complex operations, the study is the use SAS and MATLAB programming language development, the third step, for the program to be converted, to compare the initial efficiency, the fourth step, to ensure that the program did not increase the complexity of the case, to make SAS program convert MATLAB program, the fifth step, develop distributed computing program, the sixth step, experiment, finally, efficiency analysis and discussion of distributed computing model.
    Appears in Collections:[資訊管理研究所] 博碩士論文

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