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TCP and RDMA are Killing Inference Throughput; Homa can Fix It

Conference Context

Session Description

Modern AI inferencing is shifting from monolithic requests to complex agentic workflows and disaggregated KV stores. As a result, AI network traffic is no longer just very large transfers; tiny metadata requests are becoming more and more common, and their latency has a critical impact on throughput. Unfortunately, legacy transport protocols such as TCP and RDMA perform poorly on these workloads due to poor congestion control and head-of-line blocking. This talk will discuss the problems with TCP and RDMA and provide a brief introduction to the Homa transport protocol. Homa uses receiver-driven flow control and capitalizes on priority queues in network switches to reduce short-message latency by 10x for workloads like those in AI datacenters.

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Notes

Synthesis

Synthesized Breakdown

TCP and RDMA are Killing Inference Throughput; Homa can Fix It ## Conference Context - Date/time: 2026-07-01 · 9:20am-9:40am - Track/room: Software Factories · Main Stage - Speaker(s): John Ousterhout - Session type/status: keynote · confirmed - Track: Software Factories - Room: Main Stage - Session type: keynote - Status: confirmed ## Session Description Modern AI inferencing is shifting from monolithic requests to complex agentic workflows and disaggregated KV stores. As a result, AI network traffic is no longer just very large transfers; tiny metadata requests are becoming more and more common, and their latency has a critical impact on throughput. Unfortunately, legacy transport protocols such as TCP and RDMA perform poorly on these workloads due to poor congestion control and head-of-line blocking. This talk will discuss the problems with TCP and RDMA and provide a brief introduction to the Homa transport protocol.

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Topics Covered

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Novel Concepts / Clever Methods

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