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Conflict prediction-based transaction execution for transactional memory in multi-core in-memory databases

  • Min Yoon
  • , Moon Hwan Kang
  • , Yeon Woo Jang
  • , Jae Woo Chang*
  • *Corresponding author for this work
    • Jeonbuk National University

    Research output: Contribution to conferenceConference paperpeer-review

    Abstract

    This paper proposed a novel hybrid transactional memory(HyTM) that exploits the benefits of both Haswell's RTM(restricted transactional memory) and software transactional memory(STM). Unlike the existing HyTMs, the proposed HyTM can predict and resolve conflicts between transaction running concurrently by using a prediction matrix and transaction metadata. Also the proposed HyTM can provide the optimal HTM configuration for a given workload by computing the optimal retry threshold based on deep learning algorithms.

    Original languageEnglish
    Title of host publicationProceedings - 2016 IEEE International Conference on Cluster Computing, CLUSTER 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages148-149
    Number of pages2
    ISBN (Electronic)9781509036530
    DOIs
    StatePublished - 2016.12.6
    Event2016 IEEE International Conference on Cluster Computing, CLUSTER 2016 - Taipei, Taiwan, Province of China
    Duration: 2016.09.132016.09.15

    Publication series

    NameProceedings - IEEE International Conference on Cluster Computing, ICCC
    ISSN (Print)1552-5244

    Conference

    Conference2016 IEEE International Conference on Cluster Computing, CLUSTER 2016
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period16.09.1316.09.15

    Keywords

    • Concurrency control
    • HTM
    • In-memory database
    • Multi-core
    • STM
    • Transactional memory

    Quacquarelli Symonds(QS) Subject Topics

    • Computer Science & Information Systems
    • Data Science

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