Enhanced ECMP for AI Cluster
draft-cheng-rtgwg-enhanced-ecmp-00
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
|
|
|---|---|---|---|
| Authors | Weiqiang Cheng , Changwang Lin | ||
| Last updated | 2026-01-07 (Latest revision 2025-07-06) | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
In AI training scenarios, the current mainstream load balancing technology is per-flow ECMP. However, hash collision issues lead to imbalanced traffic distribution, adversely affecting application performance. To address this problem, this document proposes an enhanced ECMP method that resolves load imbalance caused by hash collisions. The proposed solution effectively improves load balancing efficiency, reduces network congestion, and enhances overall network performance.
Authors
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)