Understanding QUIC's Throughput Speedbumps

QUIC is experiencing phenomenal success as a low-latency, secure, and flexible protocol, adopted and deployed by multiple hyperscale content providers. However, the throughput of all its implementations remains remarkably low compared to that of TCP + TLS. Approaches to accelerating QUIC's throughput remain scattered, applied to a single implementation at a time, and one approach at a time. In this paper, we systematically identify the different bottlenecks that arise in different implementations. We use our findings to propose an application-agnostic architecture to accelerate single-connection throughput in QUIC. We demonstrate the value of our proposal by accelerating two implementations: quicly and mvfst, improving their throughput by 1.36× and 1.88× respectively, compared to their baseline implementations.

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Publication Details

Published
2025-07-14
DOI
https://doi.org/10.1145/3744200.3744780
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

Understanding QUIC's Throughput Speedbumps

Ahmed Saeed, S. Mukherjee, Demi Lei, Mostafa Ammar
Parallel Computing and Optimization Techniques
article

Understanding QUIC's Throughput Speedbumps

Ahmed Saeed, S. Mukherjee, Demi Lei, Mostafa Ammar
article en

Abstract

QUIC is experiencing phenomenal success as a low-latency, secure, and flexible protocol, adopted and deployed by multiple hyperscale content providers. However, the throughput of all its implementations remains remarkably low compared to that of TCP + TLS. Approaches to accelerating QUIC's throughput remain scattered, applied to a single implementation at a time, and one approach at a time. In this paper, we systematically identify the different bottlenecks that arise in different implementations. We use our findings to propose an application-agnostic architecture to accelerate single-connection throughput in QUIC. We demonstrate the value of our proposal by accelerating two implementations: quicly and mvfst, improving their throughput by 1.36× and 1.88× respectively, compared to their baseline implementations.

Georgia Institute of Technology (US)
Openalex Percentile: Top 83%
Parallel Computing and Optimization Techniques
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