Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 158 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 29 tok/s Pro
GPT-5 High 29 tok/s Pro
GPT-4o 117 tok/s Pro
Kimi K2 182 tok/s Pro
GPT OSS 120B 439 tok/s Pro
Claude Sonnet 4.5 38 tok/s Pro
2000 character limit reached

An Extensible Software Transport Layer for GPU Networking (2504.17307v1)

Published 24 Apr 2025 in cs.NI

Abstract: Fast-evolving ML workloads have increasing requirements for networking. However, host network transport on RDMA NICs is hard to evolve, causing problems for ML workloads. For example, single-path RDMA traffic is prone to flow collisions that severely degrade collective communication performance. We present UCCL, an extensible software transport layer to evolve GPU networking. UCCL decouples the data path and control path of existing RDMA NICs and efficiently runs the control-path transport on host CPUs. This software extensibility brings in transport innovations that cannot be achieved in hardware for ML workloads, e.g., a multipath transport to resolve flow collisions. ML collectives atop UCCL achieve up to 3.3x higher performance compared to an industry solution.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 3 tweets and received 1 like.

Upgrade to Pro to view all of the tweets about this paper: