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2019 | OriginalPaper | Buchkapitel

Automated Hot_Text and Huge_Pages: An Easy-to-Adopt Solution Towards High Performing Services

verfasst von : Zhenyun Zhuang, Mark Santaniello, Shumin Zhao, Bikash Sharma, Rajit Kambo

Erschienen in: Web Services – ICWS 2019

Verlag: Springer International Publishing

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Abstract

Performance optimizations of large scale services can lead to significant wins on service efficiency and performance. CPU resource is one of the most common performance bottlenecks, hence improving CPU performance has been the focus of many performance optimization efforts. In particular, reducing iTLB (instruction TLB) miss rates can greatly improve CPU performance and speed up service running.
At Facebook, we have achieved CPU reduction by applying a solution that firstly identifies hot-text of the (software) binary and then places the binary on huge pages (i.e., 2 MB+ memory pages). The solution is wrapped into an automated framework, enabling service owners to effortlessly adopt it. Our framework has been applied to many services at Facebook, and this paper shares our experiences and findings.

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Fußnoten
1
Please refer to Sect. 2 for detailed explanations of iTLB misses.
 
2
We observed that most services are relatively stable with regard to hot functions, hence weekly profiling suffices.
 
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Metadaten
Titel
Automated Hot_Text and Huge_Pages: An Easy-to-Adopt Solution Towards High Performing Services
verfasst von
Zhenyun Zhuang
Mark Santaniello
Shumin Zhao
Bikash Sharma
Rajit Kambo
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-23499-7_10

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