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姓名 邱建豪(Jian-hao Chiou)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 一個建立在平行工作系統上的動態全球計算平台
(A Dynamic Worldwide Computing Paltform on Job-Parallel Computing System)
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摘要(中) 平行工作計算(Job-Parallel Computing)式的網格系統將每個需要執行的程式當成工作(Job)送往網格上適合的機器上面執行,其優點就是管理容易而且程式不必重寫即可在網格上執行,缺點則是無法在計算期間使用複雜的通訊而限制其可程式化的能力。相反的,全球計算(Worldwide Computing)式的網格系統透過網路與虛擬機器(Virtual Machine)的技術,將所有的異質性計算資源整合成一個具有單一性質計算平台。這種網格系統提供強大的通訊、同步與分散式計算、動態系統重組等等功能。
在本論文中,我們提出一個嶄新的網格計算系統- 一個建立在平行工作系統上的動態全球計算平台。這個計算平台將Condor(一種平行工作計算網格系統)當成系統的主骨幹,然後把SALSA (一種全球計算系統) 的虛擬機器與SALSA 應用程式一起上傳到Condor 上的不特定計算資源上面執行。因此這種計算架構將具有更大的彈性、管理容易、而且可保有全球計算的各項優點。我們的作法是利用Condor 的工具將可以使用的計算資源整合成可執行的一個集合,也就是Condor Pool,再建立一個即時監控與管理虛擬機器與
摘要(英) A job-parallel grid system considers each program to be executed as a job,and looks for available computing resources for the job. The major advantages of a job-parallel grid system are: (1) job execution can be easily handled by users, and (2) executable files can be submitted to the system without program re-engineering. The disadvantage is that its programmability is not good enough to support advanced communication primitives. On the contrary, a worldwide computing grid system utilizes the power of the internet and the technology of virtual machines to integrate heterogeneous computing resources as a whole. It provides high-level communication primitives for better programmability, supports numerous coordination approaches for distributed computing, and enables dynamic system reconfiguration for dynamic load-balancing.
In this paper, we suggest a novel, dynamic worldwide computing platform which operates on a task-parallel computing system. The proposed platform uses Condor, a task-parallel computing system, as its fundamental infrastructure, and it submits the virtual machines of SALSA, which is a worldwide computing system, along with the SALSA applications to the Condor system for execution. The proposed platform will be more flexible, more manageable, and runs as a complete worldwide computing platform because it is actually a system of two faces. To construct the proposed platform, we will use Condor to build a Condor pool (a set of computing resources) first.Consequently, we will devise a mechanism to detect and manage virtual machines on the Condor Pool and SALSA applications on virtual machines. Then we will implement necessary interface to shorten the gap between the users and our system. Our goal is to integrate the advantages of job-parallel computing and worldwide computing, develop one new grid computing platform.
關鍵字(中) ★ 全球計算
★ 分散式計算
★ 網格計算
關鍵字(英) ★ grid computing
★ condor
★ worldwide computing
論文目次 摘要 i
Abstract ii
謝誌 iv
目錄 v
圖目錄 vii
表目錄 ix
第一章 緒論 1
1.1  研究背景 1
1.2  研究動機 5
1.3  研究目的 7
1.4 研究問題與對策 7
1.5  章節安排 8
第二章 相關背景 9
2.1  Job-Parallel System:Condor 9
2.1.1 The Architecture of Condor 10
2.1.2 Disadvantage of Condor 14
2.2  Distributed Programming Language:SALSA 14
2.3  Condor與 SALSA的比較 19
第三章 系統執行環境的設計 22
3.1  Virtual Machine Naming Service 24
3.2  Environment Status Report Service 26
3.3  Worldwide Computing應用程式的轉移。 29
第四章 系統實作 32
4.1  Condor Pool的建立 32
4.2  虛擬機器命名服務 (Virtual Machine Naming Service) 35
4.3  Environment Status Report Service 40
4.4  應用程式的轉移 43
4.5  Pseudo Code of Naming Server, Client and Query 45
4.5.1 Naming Server 45
4.5.2 Client 47
4.5.3 Query 48
第五章 結論與未來展望 49
參考文獻 51
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[2] I. Foster and C. Kesselman. The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2003
[3] Condor World Map, http://www.cs.wisc.edu/condor/map/
[4] NASA Advanced Supercomputing(NAS), http://www.nas.nasa.gov
[5] Map-Reduce, Jeffrey Dean, Sanjay Ghemawat, MapReduce: Simplified Data Processing on Large Clusters. Google, Inc.
[6] Nicholas Coleman, Rajesh Raman, Miron Livny and Marvin Solomon, Distributed Policy Management and Comprehension with Classified Advertisements, University of Wisconsin-Madison Computer Sciences Technical Report #1481, April 2003.
[7] Nicholas Coleman, An Implementation of Matchmaking Analysis in Condor, Masters' Project report, University of Wisconsin, Madison, May 2001.
[8] Agha, G. Concurrent object-oriented programming. Commun. ACM 33, 9 (Sept. 1990), 125–141.
[9] Anderson, D.P., Christensen, C., Allen, B.. Designing a Runtime System for Volunteer Computing. Supercomputing, 2006. SC '06. Proceedings of the ACM/IEEE SC 2006 Conference, vol., no., pp.33-33, 11-17 Nov. 2006
[10] JPMordon, http://www.jpmorgan.com/pages/jpmorgan
[11] P. Avery and I. Foster. The GriPhyN project: Toward petascale virtual data grids. Available: http://www.griphyn.org, 2001
[12] David P. Anderson , Jeff Cobb , Eric Korpela , Matt Lebofsky , Dan Werthimer. SETI@home: an experiment in public-resource computing, Communications of the ACM, v.45 n.11, p.56-61, November 2002.
[13] Jamali, N., Thati, P., and Agha, G. An actor-based architecture for customizing and controlling agent ensembles. IEEE Intelligent Systems 14, 2 (Apr. 1999), 38–44.
[14] Michael Litzkow, Todd Tannenbaum, Jim Basney, and Miron Livny, Checkpoint and Migration of UNIX Processes in the Condor Distributed Processing System, University of Wisconsin-Madison Computer Sciences Technical Report 1346, April 1997.
[15] Carlos A. Varela, Gul Agha, Wei-Jen Wang, Travis Desell, Kaoutar El Maghraoui, Jason LaPorte, and Abe Stephens. 2007. The SALSA Programming Language 1.1.2 Release Tutorial. Technical report 07-12, Dept. of Computer Science, R.P.I..
[16] Andrew S. Grimshaw, Wm. A. Wulf, and CORPORATE The Legion Team. The legion vision of a worldwide virtual computer. Commun. ACM, 40(1):39–45, 1997.
[17] Hadoop, http://hadoop.apache.org/core/
[18] D. Jewitt. Project Pan-STARRS and the Outer Solar System. Earth, Moon and Planets, 92, 465-476, 2004.
[19] Map-Reduce, Jeffrey Dean, Sanjay Ghemawat, MapReduce: Simplified Data Processing on Large Clusters. Google, Inc.
[20] Carlos A. Varela, Paolo Ciancarini, and Kenjiro Taura, editors. Scientific Programming Journal Special Issue on Dynamic Grids and Worldwide Computing, volume 13. IOS Press, Amsterdam, December 2005.
[21] Ming Xu, Zhenhua Hu, Weihong Long, and Wayne Liu. Service virtualization: Infrastructure and applications. In Ian Foster and Carl Kesselman, editors, The Grid: Blueprint for a New Computing Infrastructure (Second Edition). Morgan Kaufmann, 2004.
[22] Travis Desell, Nathan Cole, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski, and Carlos Varela. Distributed and Generic Maximum Likelihood Evaluation. In 3rd IEEE International Conference on e-Science and Grid Computing (eScience2007), Bangalore, India, pages 8pp, December 2007
[23] W. Wang, K. E. Maghraoui, J. Cummings, J. Napolitano, B. Szymanski, and C. Varela. A middleware framework for maximum likelihood evaluation over dynamic grids. In Second IEEE International Conference on e-Science and Grid Computing, page 8 pp, Amsterdam, Netherlands, December 2006.
[24] Goux, J., Kulkarni, S., Yoder, M., and Linderoth, J. 2000. An Enabling Framework for Master-Worker Applications on the Computational Grid. In Proceedings of the 9th IEEE international Symposium on High Performance Distributed Computing (August 01 - 04, 2000). High Performance Distributed Computing. IEEE Computer Society, Washington, DC, 43.
[25] Condor, http://www.cs.wisc.edu/condor/
[26] Douglas Thain, Todd Tannenbaum, and Miron Livny, Distributed Computing in Practice: The Condor Experience Concurrency and Computation: Practice and Experience, Vol. 17, No. 2-4, pages 323-356, February-April, 2005.
[27] James Frey, Todd Tannenbaum, Miron Livny, Ian Foster, Steven Tuecke. Condor-G: A Computation Management Agent for MultiInstitutional Grids, Proceedings of the Tenth IEEE Symposium on High Performance Distributed Computing (HPDC10).
[28] PBS GridWorks, http://www.pbsgridworks.com/Default.aspx
[29] Globus. http://www.globus.org/.
指導教授 王尉任(Wei-ren Wang) 審核日期 2009-7-21
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