面向大规模Web服务的HHVM性能优化

Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering Pub Date : 2023-04-15 DOI:10.1145/3578244.3583720

Yuhao Li, Abhishek Gupta, Alex Yang, Peinan Chen, Joey Pinto, B. Karrer, Mayank Pundir, M. Balandat, A. Kejariwal, Benjamin Lee

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引用次数: 0

摘要

HHVM通常是为大型在线web服务开发的，但HHVM的性能仍有很大的优化空间。本文讨论了为Meta的web服务优化HHVM性能所面临的挑战和技术。我们首先评估语义请求路由的有效性，语义请求路由是一种旨在提高HHVM中代码缓存性能的请求路由方法，并研究其对优化HHVM性能的影响。其次，我们对大规模数据中心的HHVM性能进行了表征，并确定了不可控混杂因素带来的挑战。最后，我们提出了用于大规模自动调优HHVM性能的性能管理框架。

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HHVM Performance Optimization for Large Scale Web Services

HHVM is commonly developed for large online web services, yet there remains much room for optimizing HHVM performance. This paper discusses challenges and techniques in optimizing HHVM performance for Meta's web service. We begin by evaluating the effectiveness of semantic request routing, a request routing method aimed at enhancing code cache performance in HHVM, and examine its implications for optimizing HHVM performance. Second, we characterize HHVM performance for a large-scale datacenter and identify the challenges brought by uncontrollable confounding factors. Finally, we present the performance management framework for autotuning HHVM performance at scale.

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Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering

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