An efficient parallel termination detection algorithm

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Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Of ... continued below

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Baker, A H; Crivelli, S & Jessup, E R May 27, 2004.

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Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Of these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.

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PDF-file: 15 pages; size: 0 Kbytes

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  • Journal Name: International Journal of Parallel, Emergent and Distributed Systems; Journal Volume: 21; Journal Issue: 4

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  • Report No.: UCRL-JRNL-204452
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 888629
  • Archival Resource Key: ark:/67531/metadc885323

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  • May 27, 2004

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  • Sept. 21, 2016, 2:29 a.m.

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  • Nov. 23, 2016, 5:44 p.m.

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Baker, A H; Crivelli, S & Jessup, E R. An efficient parallel termination detection algorithm, article, May 27, 2004; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc885323/: accessed August 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.