MCMalloc: A scalable memory allocator for multithreaded applications on a many-core shared-memory machine

Akira Umayabara, Hayato Yamana

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In the big data era, multithreaded processing on a many-core machine, whose core number is still increasing, has become essential to parallelize the execution of big data applications, besides distributed computing. In such a machine, malloc-intensive applications cannot scale due to lock contentions among threads, which becomes worse as the number of threads increases. To solve the problem, we propose a new method to reduce lock contentions by batch malloc, pseudo free, and fine-grained data-locking. Experimental result shows 4.72 times speed-up in comparison with JEmalloc which is the fastest memory allocator among previous ones.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
EditorsJian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4846-4848
Number of pages3
ISBN (Electronic)9781538627143
DOIs
Publication statusPublished - 2017 Jul 1
Event5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States
Duration: 2017 Dec 112017 Dec 14

Publication series

NameProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume2018-January

Other

Other5th IEEE International Conference on Big Data, Big Data 2017
CountryUnited States
CityBoston
Period17/12/1117/12/14

Keywords

  • Memory Allocator
  • many-core

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Control and Optimization

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