Ptlbmalloc2: Reducing TLB shootdowns with high memory efficiency

Stijn Schildermans, Kris Aerts, Jianchen Shan, Xiaoning Ding

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

2 Scopus citations

Abstract

The cost of TLB consistency is steadily increasing as we evolve towards ever more parallel and consolidated systems. In many cases the application memory allocator is responsible for much of this cost. Existing allocators to our knowledge universally address this issue by sacrificing memory efficiency. This paper shows that such trade-offs are not necessary by presenting a novel memory allocator that exhibits both excellent memory efficiency and (TLB) scalability: ptlbmalloc2. First, we show that TLB consistency is becoming a major scalability bottleneck on modern systems. Next, we describe why existing memory allocators are unsatisfactory regarding this issue. Finally, we present and evaluate ptlbmalloc2, which has been implemeted as a library on top of glibc. Ptlbmalloc2 outperforms glibc by up to 70% in terms of cycles and execution time with a negligible impact on memory efficiency for real-world workloads. These results provide a strong incentive to rethink memory allocator scalability in the current era of many-core NUMA systems and cloud computing.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE International Symposium on Parallel and Distributed Processing with Applications, 2020 IEEE International Conference on Big Data and Cloud Computing, 2020 IEEE International Symposium on Social Computing and Networking and 2020 IEEE International Conference on Sustainable Computing and Communications, ISPA-BDCloud-SocialCom-SustainCom 2020
EditorsJia Hu, Geyong Min, Nektarios Georgalas, Zhiwei Zhao, Fei Hao, Wang Miao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages76-83
Number of pages8
ISBN (Electronic)9781665414852
DOIs
StatePublished - Dec 2020
Externally publishedYes
Event18th IEEE International Symposium on Parallel and Distributed Processing with Applications, 10th IEEE International Conference on Big Data and Cloud Computing, 13th IEEE International Symposium on Social Computing and Networking and 10th IEEE International Conference on Sustainable Computing and Communications, ISPA-BDCloud-SocialCom-SustainCom 2020 - Virtual, Exeter, United Kingdom
Duration: Dec 17 2020Dec 19 2020

Publication series

NameProceedings - 2020 IEEE International Symposium on Parallel and Distributed Processing with Applications, 2020 IEEE International Conference on Big Data and Cloud Computing, 2020 IEEE International Symposium on Social Computing and Networking and 2020 IEEE International Conference on Sustainable Computing and Communications, ISPA-BDCloud-SocialCom-SustainCom 2020

Conference

Conference18th IEEE International Symposium on Parallel and Distributed Processing with Applications, 10th IEEE International Conference on Big Data and Cloud Computing, 13th IEEE International Symposium on Social Computing and Networking and 10th IEEE International Conference on Sustainable Computing and Communications, ISPA-BDCloud-SocialCom-SustainCom 2020
Country/TerritoryUnited Kingdom
CityVirtual, Exeter
Period12/17/2012/19/20

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Renewable Energy, Sustainability and the Environment
  • Computational Mathematics
  • Social Sciences (miscellaneous)
  • Communication
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

Keywords

  • Memory allocator
  • Memory efficiency
  • Performance
  • TLB
  • TLB shootdowns

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