I-D Action: draft-calabria-bmwg-ai-fabric-training-bench-04.txt

Internet-Draft draft-calabria-bmwg-ai-fabric-training-bench-04.txt is now
available.

   Title:   Benchmarking Methodology for AI Training Network Fabrics
   Authors: Fernando Calabria
            Carlos Pignataro
            Qin Wu
            Giuseppe Fioccola
            Sowjanya Reddy
   Name:    draft-calabria-bmwg-ai-fabric-training-bench-04.txt
   Pages:   50
   Dates:   2026-08-12

Abstract:

   This document defines benchmarking terminology, methodologies, and
   Key Performance Indicators (KPIs) for evaluating Ethernet-based AI
   training network fabrics.

   As large-scale distributed Artificial Intelligence / Machine Learning
   (AI/ML) training clusters grow to tens of thousands of accelerators
   (GPUs or generic accelerator processing units (XPUs)), the backend
   network fabric determines Job Completion Time (JCT), training
   throughput, and accelerator utilization.

   This document establishes vendor-independent, reproducible test
   procedures for benchmarking fabric-level performance under realistic
   AI training workloads.  The tests cover Remote Direct Memory Access
   (RDMA) over Converged Ethernet version 2 (RoCEv2) transport, the
   Ultra Ethernet Transport (UET) protocol defined by the Ultra Ethernet
   Consortium (UEC) Specification 1.0, congestion management (Priority
   Flow Control (PFC), Explicit Congestion Notification (ECN), Data
   Center Quantized Congestion Notification (DCQCN), Credit-Based Flow
   Control (CBFC)), load balancing strategies (Equal-Cost Multi-Path
   (ECMP), Dynamic Load Balancing (DLB), packet spraying), collective
   communication patterns (AllReduce, AllToAll, AllGather), and scale/
   soak testing.

   The methodology enables direct, reproducible comparison across switch
   ASICs, NIC transport stacks (RoCEv2 and UET), and fabric
   architectures (2-tier Clos, 3-tier Clos, and rail-optimized).

The IETF datatracker status page for this Internet-Draft is:
https://datatracker.ietf.org/doc/draft-calabria-bmwg-ai-fabric-training-bench/

There is also an HTML version available at:
https://www.ietf.org/archive/id/draft-calabria-bmwg-ai-fabric-training-bench-04.html

A diff from the previous version is available at:
https://author-tools.ietf.org/iddiff?url2=draft-calabria-bmwg-ai-fabric-training-bench-04

Internet-Drafts are also available by rsync at:
rsync.ietf.org::internet-drafts


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