License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.OPODIS.2019.10
URN: urn:nbn:de:0030-drops-117965
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/11796/
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Chen, Zhanhao ; Hassan, Ahmed ; Kishi, Masoomeh Javidi ; Nelson, Jacob ; Palmieri, Roberto

HaTS: Hardware-Assisted Transaction Scheduler

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LIPIcs-OPODIS-2019-10.pdf (0.8 MB)

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.

BibTeX - Entry

@InProceedings{chen_et_al:LIPIcs:2020:11796,
  author =	{Zhanhao Chen and Ahmed Hassan and Masoomeh Javidi Kishi and Jacob Nelson and Roberto Palmieri},
  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 =	{Pascal Felber and Roy Friedman and Seth Gilbert and Avery Miller},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/11796},
  URN =		{urn:nbn:de:0030-drops-117965},
  doi =		{10.4230/LIPIcs.OPODIS.2019.10},
  annote =	{Keywords: Transactions, Scheduling, Hardware Transactional Memory}
}

Keywords: Transactions, Scheduling, Hardware Transactional Memory
Collection: 23rd International Conference on Principles of Distributed Systems (OPODIS 2019)
Issue Date: 2020
Date of publication: 11.02.2020

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