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Efficient vector-descriptor product exploiting time-memory trade-offs

Published: 21 December 2011 Publication History

Abstract

The description of large state spaces through stochastic structured modeling formalisms like stochastic Petri nets, stochastic automata networks and performance evaluation process algebra usually represent the infinitesimal generator of the underlying Markov chain as a Kronecker descriptor instead of a single large sparse matrix. The best known algorithms used to compute iterative solutions of such structured models are: the pure sparse solution approach, an algorithm that can be very time efficient, and almost always memory prohibitive; the Shuffle algorithm which performs the product of a descriptor by a probability vector with a very impressive memory efficiency; and a newer option that offers a trade-off between time and memory savings, the Split algorithm. This paper presents a comparison of these algorithms solving some examples of structured Kronecker represented models in order to numerically illustrate the gains achieved considering each model's characteristics.

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  • (2013)Analysis of exponential reliable production lines using Kronecker descriptorsInternational Journal of Production Research10.1080/00207543.2012.75455051:14(4240-4257)Online publication date: Jul-2013
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Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 39, Issue 3
December 2011
163 pages
ISSN:0163-5999
DOI:10.1145/2160803
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 December 2011
Published in SIGMETRICS Volume 39, Issue 3

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Author Tags

  1. kronecker products
  2. numerical methods
  3. optimization of iterative methods

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Cited By

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  • (2016)Stochastic Performance Analysis of Global Software Development TeamsACM Transactions on Software Engineering and Methodology10.1145/295509325:3(1-32)Online publication date: 22-Aug-2016
  • (2013)Symbolic Solution of Kronecker-Based Structured Markovian ModelsProceedings of the 2013 IEEE 21st International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems10.1109/MASCOTS.2013.62(409-413)Online publication date: 14-Aug-2013
  • (2013)Analysis of exponential reliable production lines using Kronecker descriptorsInternational Journal of Production Research10.1080/00207543.2012.75455051:14(4240-4257)Online publication date: Jul-2013
  • (2013)A Structured Stochastic Model for Prediction of Geological Stratal Stacking PatternsElectronic Notes in Theoretical Computer Science (ENTCS)10.1016/j.entcs.2013.07.003296(27-42)Online publication date: 1-Aug-2013
  • (2013)Exact Analysis of Discrete Part Production Lines: The Markovian Queueing Network and the Stochastic Automata Networks FormalismsHandbook of Stochastic Models and Analysis of Manufacturing System Operations10.1007/978-1-4614-6777-9_3(73-113)Online publication date: 1-Apr-2013
  • (2012)Performance evaluation of OpenMP-based algorithms for handling Kronecker descriptorsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2012.02.00172:5(678-692)Online publication date: 1-May-2012
  • (2011)Structured Markovian models for discrete spatial mobile node distributionJournal of the Brazilian Computer Society10.1007/s13173-010-0026-y17:1(31-52)Online publication date: 12-Jan-2011

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