How to diagnose nanosecond network latencies in rich end-host stacks


Roni Haecki, ETH Zurich; Radhika Niranjan Mysore, Lalith Suresh, Gerd Zellweger, Bo Gan, Timothy Merrifield, and Sujata Banerjee, VMware; Timothy Roscoe, ETH Zurich


Low-latency network stacks have brought down network latencies within end-hosts to the microsecond-regime. However, end-host profilers have such high overheads that they are useful only to confirm a hypothesis, not to diagnose a problem in the first place. Indeed, every one of twenty low-latency network projects we surveyed rolled their own analysis tools instead of using an existing profiler.

This paper shows how to build a latency diagnosis tool with full-stack coverage and low overhead that can identify, not just confirm, sources of latency in end hosts. The unique measurement methodology reconstructs network-message lifetimes within end hosts with nanosecond precision, by reconciling CPU and NIC hardware profiling traces across multiple time domains (network and CPU). It uncovers unexpected latency sources in both kernel and user-space stacks.

We demonstrate these capabilities by using our implementation, NSight, to systematically identify and remove performance overheads in memcached, reducing 99.9th percentile latency by a factor of 40 from 2:2 ms to 41 μs.

NSDI '22 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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@inproceedings {278368,
author = {Roni Haecki and Radhika Niranjan Mysore and Lalith Suresh and Gerd Zellweger and Bo Gan and Timothy Merrifield and Sujata Banerjee and Timothy Roscoe},
title = {How to diagnose nanosecond network latencies in rich end-host stacks},
booktitle = {19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22)},
year = {2022},
isbn = {978-1-939133-27-4},
address = {Renton, WA},
pages = {861--877},
url = {},
publisher = {USENIX Association},
month = apr

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