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4 edition of Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system found in the catalog.

Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system

Anurag Kumar

Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system

by Anurag Kumar

  • 334 Want to read
  • 2 Currently reading

Published by Dept. of Electrical Communication Engineering, Indian Institute of Science in Bangalore .
Written in English

    Subjects:
  • Stochastic programming.,
  • Computer networks.,
  • Electronic mail systems.

  • Edition Notes

    StatementAnurag Kumar and Rajeev Shorey.
    SeriesTechnical report / Education & Research Network Project ;, no. ERNET-IISc-1990.5, Technical report (Education & Research Network Project (Indian Institute of Science, Bangalore. Dept. of Electrical Communication Engineering)) ;, no. ERNET-IISc-1990.5.
    ContributionsEducation & Research Network Project (Indian Institute of Science, Bangalore. Dept. of Electrical Communication Engineering)
    Classifications
    LC ClassificationsMicrofiche 2001/60503 (T)
    The Physical Object
    FormatMicroform
    Pagination13 leaves
    Number of Pages13
    ID Numbers
    Open LibraryOL3975444M
    LC Control Number2001292951

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    Deterministic Catastrophe theory is introduced first. Then it is shown how the theory can be applied in a stochastic framework, which is useful for understanding computer system performance models. Computer system models that exhibit stochastic cusp catastrophe behavior are then analyzed. My application is " Aerodynamic Inverse Design and Analysis for a Full Engine". I use PVM to run this application on two CRAY C90s. My host is an IBM RS6K I use PVMe on an IBM SP nodes at NASA Ames. After a problematic installation of PVMe on the SP2 (it was creating a lot of orphan jobs) now runs excellently.

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Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system by Anurag Kumar Download PDF EPUB FB2

Multi-class Fork-Join queues are extension of single-class Fork-Join queues. In a multi-class Fork-Join queuing system, different types of jobs arrive, and then split into several : S. Ding. () Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system. IEEE Transactions on Parallel and Distributed Systems() Optimal service control of a station connected with two parallel by: C.P.

Kruskal and A. Weiss, Allocating independent subtasks on parallel processors, IEEE Trans, on Software Engrg. SE () [13] A. Kumar and R. Shorey, Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system, lEEETrans.

Parallel and Distributed Systems 4 () [14] : E. Bach, Rajesh K. Mansharamani, John C. Strikwerda. Stochastic-Based Robust Dynamic Resource Allocation in a Heterogeneous Computing System.

“Performance analysis and scheduling. of stochastic fork-join jobs in a multicomputer system,” T rans. ing key performance metrics. However, until today an exact analysis of FJ queueing systems in a general setup remains Fork Input Job Task Server 1 Map Combine Server 2 2 Map Combine Server N Map Combine compressed size S Task compressed sizeTasks S N Fork Input Job rs rs S 2Author: Wasiur R.

KhudaBukhsh, Amr Rizk, Alexander Frömmgen, Heinz Koeppl. Performance analysis and scheduling of stochastic fork-join jobs in a multicomputer system IEEE Transactions on Parallel and Distributed Systems, Vol.

4, No. Cited by: J Anurag Kumar and Rajeev Shorey,“Performance Analysis and Scheduling of Stochas- tic Fork-Join Jobs in a Multicomputer System”, IEEE Transactions on Parallel and Distributed Systems, Vol. 4, No. 10, pp.October Abstract.

Recently HP Labs engaged in a joint project with DreamWorks Animation to develop a Utility Rendering Service that was used to render part of the computer-animated feature film Shrek a companion paper [2] we formalized the problem of scheduling animation rendering jobs and demonstrated that the general problem is computationally intractable, as are severely restricted Cited by: Abstract.

Motivated by emerging trends and applications such as autonomic computing, this chapter presents an overview of some research in the stochastic analysis and optimization of Cited by: 7. Katayama T and Kobayashi K Performance analysis of an M/G/1 satellite node with urgent jobs of a central processing node Proceedings of the 4th International Conference on Queueing Theory and Network Applications, ().

Yann Hendel, Wieslaw Kubiak, Denis Trystram, Scheduling semi-malleable jobs to minimize mean flow time, Journal of Scheduling, v n.4, p, August Lionel Eyraud, A Pragmatic Analysis Of Scheduling Environments On New Computing Platforms, International Journal of High Performance Computing Applications, v n.4, p Cited by: ELSEVIER Performance Evaluation 19 () PERFORMANCE EVALUATION An International Journal Invited paper Application scheduling and processor allocation in multiprogrammed parallel processing systems K.C.

Sevcik Computer Systems Research Institute, University of Toronto, 10 King's College Road, Toronto, Ont. Canada M5S 1A4 Abstract When large-scale multiprocessors for parallel Cited by: J Anurag Kumar and Rajeev Shorey,“Performance Analysis and Scheduling of Stochas-tic Fork-Join Jobs in a Multicomputer System”, IEEE Transactions on Parallel and Distributed Systems, Vol.

4, No. 10, pp.October J Probability, stochastic processes, and queueing theory: the mathematics of computer performance modeling Springer-Verlag Berlin, Heidelberg © ISBNCited by: Computer Systems Science and Engineering Volume 1, Number 4, October, Kang G. Shin and C. Krishna New Performance Measures for Design and Evaluation of Real-Time Multiprocessors Helen D.

Karatza Simulation Study of Multitasking of Open Computer System Networks. ACM SIGMETRICS Performance Evaluation Review Vol Number 4, March, Jeffrey K. Hillingsworth and Barton P. Miller Summary of the SIGMETRICS Symposium on. Scheduling in Distributed Computing Systems Dynamic scheduling assumes a continuous stochastic stream of incoming tasks.

Very little parameters are known in advance for dynamic scheduling. Obviously, it is more complex than static scheduling for implementation, but achieves better throughput.

NASA Images Solar System Collection Ames Research Center Brooklyn Museum Full text of " Languages, compilers, and run-time systems for scalable computers: 4th international workshop, LCR '98, Pittsburgh, PA, USA, Mayselected papers ".

NASA Images Solar System Collection Ames Research Center Brooklyn Museum Full text of " Vector and parallel processing--VECPAR 4th International Conference, Porto, Portugal, Juneselected papers and invited talks ". Huang C, Chen C and Lai C () Evaluation and analysis of incorporating Fuzzy Expert System approach into test suite reduction, Information and Software Technology, C, (), Online publication date: 1-Nov.

Newsgroups: Subject: The Language List V Message-ID: [email protected] From: [email protected] (Bill Kinnersley) Date: Wed, 13 Jan GMT Organization: University of Kansas Computer Science Dept Lines: [This contains all 9 parts, concatenated.] The Language List - VersionJanu Job Scheduling Strategies for Parallel Processing: 11th International Workshop, JSSPPCambridge, MA, USA, JRevised Selected Papers [19, 21] is probably the most commonly used method for scheduling parallel jobs at the present time [7].

The idea is simple: Whenever the system status changes (a new job arrives or a running.The system built based on replicated resources should generate a good performance result and an enhanced system reliability.

edited by Mullender, there is a good collection of articles on various issues of distributed system design. In the book entitled Readings in Distributed Computing Systems [7], Casavant and Singhal collected 24 survey.