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HaTS: Hardware-Assisted Transaction Scheduler

Authors: Zhanhao Chen, Ahmed Hassan, Masoomeh Javidi Kishi, Jacob Nelson, and Roberto Palmieri

Published in: LIPIcs, Volume 153, 23rd International Conference on Principles of Distributed Systems (OPODIS 2019)


Abstract
In this paper we present HaTS, a Hardware-assisted Transaction Scheduler. HaTS improves performance of concurrent applications by classifying the executions of their atomic blocks (or in-memory transactions) into scheduling queues, according to their so called conflict indicators. The goal is to group those transactions that are conflicting while letting non-conflicting transactions proceed in parallel. Two core innovations characterize HaTS. First, HaTS does not assume the availability of precise information associated with incoming transactions in order to proceed with the classification. It relaxes this assumption by exploiting the inherent conflict resolution provided by Hardware Transactional Memory (HTM). Second, HaTS dynamically adjusts the number of the scheduling queues in order to capture the actual application contention level. Performance results using the STAMP benchmark suite show up to 2x improvement over state-of-the-art HTM-based scheduling techniques.

Cite as

Zhanhao Chen, Ahmed Hassan, Masoomeh Javidi Kishi, Jacob Nelson, and Roberto Palmieri. HaTS: Hardware-Assisted Transaction Scheduler. In 23rd International Conference on Principles of Distributed Systems (OPODIS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 153, pp. 10:1-10:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{chen_et_al:LIPIcs.OPODIS.2019.10,
  author =	{Chen, Zhanhao and Hassan, Ahmed and Kishi, Masoomeh Javidi and Nelson, Jacob and Palmieri, Roberto},
  title =	{{HaTS: Hardware-Assisted Transaction Scheduler}},
  booktitle =	{23rd International Conference on Principles of Distributed Systems (OPODIS 2019)},
  pages =	{10:1--10:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-133-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{153},
  editor =	{Felber, Pascal and Friedman, Roy and Gilbert, Seth and Miller, Avery},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2019.10},
  URN =		{urn:nbn:de:0030-drops-117965},
  doi =		{10.4230/LIPIcs.OPODIS.2019.10},
  annote =	{Keywords: Transactions, Scheduling, Hardware Transactional Memory}
}
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