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

被引：0

作者：

Zhuang, Zhenyun ^{[1
]}

Santaniello, Mark ^{[1
]}

Zhao, Shumin ^{[1
]}

Sharma, Bikash ^{[1
]}

Kambo, Rajit ^{[1
]}

机构：

[1] Facebook Inc, 1 Hacker Way, Menlo Pk, CA 94025 USA

来源：

WEB SERVICES - ICWS 2019 | 2019年 / 11512卷

关键词：

Huge pages; Hot-text; Performance; iTLB miss;

D O I：

10.1007/978-3-030-23499-7_10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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., 2MB+ 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.

引用

页码：147 / 162

页数：16