Ptlbmalloc2: Reducing TLB shootdowns with high memory efficiency

Document Type

Conference Proceeding

Publication Date

12-1-2020

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.

Identifier

85108021603 (Scopus)

ISBN

[9781665414852]

Publication Title

Proceedings 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

External Full Text Location

https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00036

First Page

76

Last Page

83

Grant

V433819N

Fund Ref

National Science Foundation

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