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Adaptive Versioning in Transactional Memories

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Stabilization, Safety, and Security of Distributed Systems (SSS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11914))

Abstract

Transactional memory has been receiving much attention from both academia and industry. In transactional memory, program code is split into transactions, blocks of code that appear to execute atomically. Transactions are executed speculatively and the speculative execution is supported through data versioning and conflict detection and resolution mechanisms. Lazy versioning makes aborts fast but penalizes commits, whereas eager versioning makes commits fast but penalizes aborts. In this paper, we present an adaptive versioning approach that dynamically switches between eager and lazy versioning at runtime based on appropriate system parameters so that the performance of a transactional memory system is always better than that is obtained using either eager or lazy versioning individually. We implemented our adaptive versioning approach in the latest TinySTM distribution and extensively evaluated it through 5 micro-benchmarks and 8 complex benchmarks from STAMP and STAMPEDE suites. The results show significant benefits of our approach, giving performance improvements as much as 6.3x for execution time and as much as 170x for number of aborts.

This work is supported by the National Science Foundation grant CCF-1936450.

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Notes

  1. 1.

    The experimental results conducted on basic Adaptive showed that the number of aborts always decrease in all the benchmarks but execution time for some benchmarks increase compared to the execution times obtained using eager and lazy versioning individually.

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Authors and Affiliations

  1. Department of Computer Science, Kent State University, Kent, OH, 44242, USA

    Pavan Poudel & Gokarna Sharma

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  1. Pavan Poudel
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  2. Gokarna Sharma
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Corresponding author

Correspondence to Gokarna Sharma .

Editor information

Editors and Affiliations

  1. ETH Zurich, Zurich, Switzerland

    Mohsen Ghaffari

  2. Kent State University, Kent, OH, USA

    Mikhail Nesterenko

  3. Sorbonne University, Paris, France

    Sébastien Tixeuil

  4. CEA LIST, Gif-sur-Yvette, France

    Sara Tucci

  5. Kyushu University, Fukuoka, Japan

    Yukiko Yamauchi

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Poudel, P., Sharma, G. (2019). Adaptive Versioning in Transactional Memories. In: Ghaffari, M., Nesterenko, M., Tixeuil, S., Tucci, S., Yamauchi, Y. (eds) Stabilization, Safety, and Security of Distributed Systems. SSS 2019. Lecture Notes in Computer Science(), vol 11914. Springer, Cham. https://doi.org/10.1007/978-3-030-34992-9_22

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  • DOI: https://doi.org/10.1007/978-3-030-34992-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34991-2

  • Online ISBN: 978-3-030-34992-9

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