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A Framework for Integrating Network Information into Distributed Iterative Solution of Sparse Linear Systems

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High Performance Computing for Computational Science — VECPAR 2002 (VECPAR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2565))

Abstract

Recently, we have proposed a design of an easy-to-use network information discovery tool that can interface with a distributed application non-intrusively and without incurring much overhead. The application is notified of the network changes in a timely manner and may react to the changes by invoking the adaptation mechanisms encapsulated in notification handlers. Here we describe possible adaptations of a commonly used scientific computing kernel, distributed sparse largescale linear system solution code.

This work was supported in part by NSF under grants NSF/ACI-0000443 and NSF/INT-0003274, and in part by the Minnesota Supercomputing Institute

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References

  1. D. Andersen, D. Bansal, D. Curtis, S. Seshan, and H. Balakrishnan. System support for bandwidth management and content adaptation in Internet applications. In Proceedings of 4th Symposium on Operating Systems Design and Implementation San Diego, CA, October 2000. USENIX Association.:213–226, 2000. 437

    Google Scholar 

  2. J. Dongarra, G. Fagg, A. Geist, and J. A. Kohl. HARNESS: Heterogeneous adaptable reconfigurable NEtworked systems. pages 358–359, http://citeseer.nj.nec.com/327665.html, 1998. 437

  3. X. Fu, W. Shi, A. Akkerman, and V. Karamcheti. CANS: Composable, adaptive network services infrastructure. In Proceedings of the USENIX Symposium on Internet Technologies and Systems, 2001. 437

    Google Scholar 

  4. D. Gunter, B. Tierney, B. Crowley, M. Holding, and J. Lee. Netlogger: A toolkit for distributed system performance analysis. In Proceedings of the IEEE Mascots 2000 Conference, 2000. 437

    Google Scholar 

  5. D. Kulkarni and M. Sosonkina. Using dynamic network information to improve the runtime performance of a distributed sparse linear system solution. Technical Report UMSI-2002-10, Minnesota Supercomputer Institute, University of Minnesota, Minneapolis, MN, 2002. accepted in VECPAR 2002. 439

    Google Scholar 

  6. Z. Li, Y. Saad, and M. Sosonkina. pARMS: A parallel version of the algebraic recursive multilevel solver. Technical Report UMSI-2001-100, Minnesota Supercomputer Institute, University of Minnesota, Minneapolis, MN, 2001. 437, 439, 440, 445

    Google Scholar 

  7. B. Lowekamp, N. Miller, D. Sutherland, T. Gross, P. Steenkiste, and J. Subhlok. A resource query interface for network-aware applications. Cluster Computing, 2:139–151, 1999. 437

    Article  Google Scholar 

  8. R. T. Mills, A. Stathopoulos, and E. Smirni. Algorithmic modifications to the Jacobi-Davidson parallel eigensolver to dynamically balance external CPU and memory load. In Proceedings of the International Conference on Supercomputing 2001,Sorr ento, Italy, pages 454–463, June 18–22, 2001. 437

    Google Scholar 

  9. Y. Saad. Iterative Methods for Sparse Linear Systems. PWS publishing, New York, 1996. 439, 440, 443, 444

    MATH  Google Scholar 

  10. Y. Saad and M. Sosonkina. Distributed Schur Complement techniques for general sparse linear systems. SIAM J. Scientific Computing, 21(4):1337–1356, 1999. 439

    Article  MathSciNet  Google Scholar 

  11. Y. Saad and M. Sosonkina. Non-standard parallel solution strategies for distributed sparse linear systems. In A. Uhl P. Zinterhof, M. Vajtersic, editor, Parallel Computation: Proc. of ACPC’99, Lecture Notes in Computer Science, Berlin, 1999. Springer-Verlag. 441, 443

    Google Scholar 

  12. B. Smith, P. Bjørstad, and W. Gropp. Domain Decomposition: Parallel Multilevel Methods for Elliptic Partial Differential Equations. Cambridge University Press, New York, 1996. 439, 441

    MATH  Google Scholar 

  13. M. Snir, S. Otto, S. Huss-Lederman, D. Walker, and J. Dongarra. MPI-The complete Reference, volume 1. The MIT Press, second edition, 1998. 436

    Google Scholar 

  14. M. Sosonkina. Runtime adaptation of an iterative linear system solution to distributed environments. In Applied Parallel Computing,P ARA’2000, volume 1947 of Lecture Notes in Computer Science, pages 132–140, Berlin, 2001. Springer-Verlag. 441, 443, 444

    Google Scholar 

  15. M. Sosonkina and G. Chen. Design of a tool for providing network information to distributed applications. In Parallel Computing Technologies PACT2001, volume 2127 of Lecture Notes in Computer Science, pages 350–358. Springer-Verlag, 2001. 437

    Chapter  Google Scholar 

  16. C. Wagner. Introduction to algebraic multigrid-course notes of an algebraic multigrid. University of Heidelberg 1998/99. 440

    Google Scholar 

  17. R. Wolski. Dynamically forecasting network performance using the network weather service. Cluster Computing, 1(1):119–132, 1998. 437

    Article  Google Scholar 

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Kulkarni, D., Sosonkina, M. (2003). A Framework for Integrating Network Information into Distributed Iterative Solution of Sparse Linear Systems. In: Palma, J.M.L.M., Sousa, A.A., Dongarra, J., Hernández, V. (eds) High Performance Computing for Computational Science — VECPAR 2002. VECPAR 2002. Lecture Notes in Computer Science, vol 2565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36569-9_29

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  • DOI: https://doi.org/10.1007/3-540-36569-9_29

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  • Print ISBN: 978-3-540-00852-1

  • Online ISBN: 978-3-540-36569-3

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