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International Conference on Analytical and Stochastic Modeling Techniques and Applications

ASMTA 2009: Analytical and Stochastic Modeling Techniques and Applications pp 339–353Cite as

An Analytic Model for Optimistic STM with Lazy Locking

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5513))

Abstract

We extend an existing analytic framework for modeling software transactional memory (STM) to an optimistic STM variant in which write locks are acquired lazily. Lazy locking requires a different calculation of the transition probabilities of the underlying discrete-time Markov chain (DTMC).

Based on few relevant input parameters, like the number of concurrent transactions, the transaction lengths, the share of writing operations and the number of accessible transactional data ojects, a fixed-point iteration over closed-form analytic expressions delivers key STM performance measures, e.g., the mean number of transaction restarts and the mean number of processed steps of a transaction.

In particular, the analytic model helps to predict STM performance trends as the number of cores on multi-processors increases, but other performance trends provide additional insight into system behavior.

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Author information

Authors and Affiliations

  1. Computer Networks and Communication Systems, Universität Erlangen-Nürnberg, Erlangen, Germany

    Armin Heindl

  2. Intel Corporation Microprocessor Technology Lab, Santa Clara, CA, USA

    Gilles Pokam

Authors
  1. Armin Heindl
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  2. Gilles Pokam
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Editor information

Editors and Affiliations

  1. Faculty of Advanced Technology, University of Glamorgan, CF37 1DL, Pontypridd, UK

    Khalid Al-Begain

  2. Department TELIN, Ghent University, Sint-Pietersnieuwstraat 41, 9000, Gent, Belgium

    Dieter Fiems

  3. Budapest University of Technology and Economics, P.O. Box 91, 1521, Budapest, Hungary

    Gábor Horváth

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© 2009 Springer-Verlag Berlin Heidelberg

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Heindl, A., Pokam, G. (2009). An Analytic Model for Optimistic STM with Lazy Locking. In: Al-Begain, K., Fiems, D., Horváth, G. (eds) Analytical and Stochastic Modeling Techniques and Applications. ASMTA 2009. Lecture Notes in Computer Science, vol 5513. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02205-0_24

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  • DOI: https://doi.org/10.1007/978-3-642-02205-0_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02204-3

  • Online ISBN: 978-3-642-02205-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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