Lossless Preemptive Buffer Management via Orchestrating Inter-Switch Idle Capacity

Remote Direct Memory Access (RDMA) networks require efficient switch buffer management to maintain high throughput, low latency, and losslessness. However, limited buffer size and diverse traffic types challenge existing non-preemptive approaches (e.g., DT), often leading to buffer choking and performance degradation. We present Nomad, a lossless preemptive buffer management system that allows high-priority flows to evict lower-priority packets and redirect them to neighboring switches. Nomad involves lightweight packet eviction, enhances DT by modeling remote buffer availability into local threshold calculation, and coordinates evictions via low-cost notifications. Simulations show that Nomad reduces high-priority QCT slowdown by 21-33% over DT.

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Published
2025-09-08
DOI
https://doi.org/10.1145/3744969.3748442
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Lossless Preemptive Buffer Management via Orchestrating Inter-Switch Idle Capacity

Zhi-Hua Yan, Mingwei Xu, Ruihao Wang, Yangyang Wang
Parallel Computing and Optimization Techniques
article

Lossless Preemptive Buffer Management via Orchestrating Inter-Switch Idle Capacity

Zhi-Hua Yan, Mingwei Xu, Ruihao Wang, Yangyang Wang
article en

Abstract

Remote Direct Memory Access (RDMA) networks require efficient switch buffer management to maintain high throughput, low latency, and losslessness. However, limited buffer size and diverse traffic types challenge existing non-preemptive approaches (e.g., DT), often leading to buffer choking and performance degradation. We present Nomad, a lossless preemptive buffer management system that allows high-priority flows to evict lower-priority packets and redirect them to neighboring switches. Nomad involves lightweight packet eviction, enhances DT by modeling remote buffer availability into local threshold calculation, and coordinates evictions via low-cost notifications. Simulations show that Nomad reduces high-priority QCT slowdown by 21-33% over DT.

Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 74%
Parallel Computing and Optimization Techniques
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