<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.clad-rtgwg-ipfrr-aiml" target="https://datatracker.ietf.org/doc/html/draft-clad-rtgwg-ipfrr-aiml-00">
   <front>
      <title>IP Fast Reroute for AI/ML Fabrics</title>
      <author initials="F." surname="Clad" fullname="Francois Clad">
         <organization>Cisco Systems, Inc.</organization>
      </author>
      <author initials="C." surname="Filsfils" fullname="Clarence Filsfils">
         <organization>Cisco Systems, Inc.</organization>
      </author>
      <author initials="R." surname="Jiang" fullname="Roy Jiang">
         <organization>Alibaba</organization>
      </author>
      <author initials="D." surname="Cai" fullname="Dezhong Cai">
         <organization>Alibaba</organization>
      </author>
      <date month="March" day="2" year="2026" />
      <abstract>
	 <t>   This document describes the requirements and mechanisms for achieving
   sub-100 microsecond convergence in Artificial Intelligence (AI) Data
   Center (DC) fabrics and Data Center Interconnect (DCI) environments.
   It explores the limitations of current IP Fast Reroute (RFC 5714)
   capabilities, such as ECMP, LFA, and TI-LFA, particularly in the
   context of large-scale, multi-tier Clos topologies and BGP-only
   fabrics.  The draft highlights the requirements for hardware-
   accelerated network notification mechanisms and congestion-aware
   remote protection strategies to address the stringent performance
   demands of AI workloads.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-clad-rtgwg-ipfrr-aiml-00" />
   
</reference>
