extensible computing 中文意思是什麼
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The portable, extensible toolkit for scientific computation, petsc, has become a model of the high performance numerical software which gains huge attention and wide use in commuting community throughout the world. our selection of petsc as the target model of studying is based on following reasons : petsc uses mpi for all parallel communication, which is most fittable for general scalable computing, especially on our pc - cluster platform. petsc is a general purpose suite : of tools for the scalable solution of partial differential equations and related problems, which is much in accord with our research focus
可移植、可擴展科學計算軟體包petsc是近來在國際上很受關注、應用廣泛的高性能并行數值軟體開發典範之一，我們對它的重點學習與研究主要出於以下考慮： petsc基於mpi并行程序設計平臺，適合於我們常用的并行計算機尤其是機群系統；它以偏微分方程、代數方程求解功能為實現重點，非常切合於我們的主要研究方向和應用需求；尤為重要的是，在其良好的軟體使用模式和執行性能下隱含的先進軟體設計思想和程序實現方案，對我們今後的數值軟體開發很有借鑒意義。 -
This paper tries to resolve this problem by redesigning the software architecture of distributing parallel schedule model to improve the system " s adaptability and extensibility. this paper is balanced as following. firstly, this paper studies the characters of distributed parallel schedule that required by the trend of distributed parallel computing and criticizes the existing solution to these problems ; secondly, this paper develops a extensible and adaptive distributing parallel schedule to resolve these problems ; finally, this paper offers three key experiments to verify the rationality of the solution and then draws conclusion
本文安排如下：首先，在引入研究問題的基礎上，討論分佈并行的調度模型所需要具備的新的特徵以及給出這些特徵的一個可計算的解決方法；然後，在此基礎上提出一種新的分佈并行調度的設計模型，該模型重點解決分佈并行調度的設計結構對可擴展性，自適應性的制約問題；接著，基於上述討論結果提出了分佈并行調度器設計和實現上的具體應用實例；最後，通過試驗的方法討論了該實際模型的性能並對本文進行簡要總結。 -
Our purpose is to develop an open, easily maintainable, extensible and user - friendly scientific data mining system ( sdms ) which can extract useful knowledge from scientific data and analyze the simulation result of scientific computing. the system is hosted on dbms and windows platform. currently a prototype system with functions of data denoise, compress, attribute reduction, discretion, classifying and clustering has been completed
科學數據具有維數高、數據量大，數據不完全，有噪聲等特點，本課題在現有的數據庫和windows平臺上，開發一個具有開放體系結構的、易擴充的、易維護的、具有良好人機交互界面的數據挖掘系統，從科學數據中提取隱含在其中的有用的知識，為科學計算中的模擬信息提供符合規律的模擬結果分析。
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