Platinum: A CPU-Efficient Concurrent Garbage Collector for Tail-Reduction of Interactive Services


Mingyu Wu, Ziming Zhao, Yanfei Yang, Haoyu Li, Haibo Chen, Binyu Zang, and Haibing Guan, Shanghai Jiao Tong University; Sanhong Li, Chuansheng Lu, and Tongbao Zhang, Alibaba


The service-oriented architecture decomposes a monolithic service into single-purpose services for better modularity and reliability. The interactive nature, plus the fact of running inside a managed runtime, makes garbage collection a key to the reduction of tail latency of such services. However, prior concurrent garbage collectors reduce stop-the-world (STW) pauses by consuming more CPU resources, which can affect the application performance, especially under heavy workload. Based on an in-depth analysis of representative latency-sensitive workloads, this paper proposes Platinum, a new concurrent garbage collector to reduce the tail latency with moderate CPU consumption. The key idea is to construct an isolated execution environment for concurrent mutators to improve application latency without interfering with the execution of GC threads. Platinum further leverages a new hardware feature (i.e., memory protection keys) to eliminate software overhead in previous concurrent collectors. An evaluation against state-of-the-art concurrent garbage collectors shows that Platinum can significantly reduce the tail latency of real-world interactive services (by as much as 79.3%) while inducing moderate CPU consumption.

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@inproceedings {254453,
author = {Mingyu Wu and Ziming Zhao and Yanfei Yang and Haoyu Li and Haibo Chen and Binyu Zang and Haibing Guan and Sanhong Li and Chuansheng Lu and Tongbao Zhang},
title = {Platinum: A {CPU-Efficient} Concurrent Garbage Collector for {Tail-Reduction} of Interactive Services},
booktitle = {2020 USENIX Annual Technical Conference (USENIX ATC 20)},
year = {2020},
isbn = {978-1-939133-14-4},
pages = {159--172},
url = {},
publisher = {USENIX Association},
month = jul

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