Hi Xiaohu,
I would be interested to learn why described elephant flows couldn't be
instead handled in typical TE fashion (choose your TE flavor) since we know
the target AI training clusters at the CLOS edges ? Such TE could steer
such flows link by link or inject it into disjoied virtual topologies.
Said this I am quite sceptical when it comes to injection of lot's of
dynamic application performance data into any routing protocol. Yes it has
been done in the past see rfc7810 and you do need to explain why
essentially similar additional data of such kind is needed.
Kind regards,
Robert
On Thu, Nov 23, 2023 at 5:27 PM xuxiaohu_i...@hotmail.com <
xuxiaohu_i...@hotmail.com> wrote:
> Hi all,
>
> Any comments or suggestions are welcome.
>
> Best regards,
> Xiaohu
>
>
>
> 发件人: internet-dra...@ietf.org
> 日期: 星期五, 2023年11月24日 00:13
> 收件人: Xiaohu Xu
> 主题: New Version Notification for draft-xu-lsr-fare-00.txt
>
> A new version of Internet-Draft draft-xu-lsr-fare-00.txt has been
> successfully
> submitted by Xiaohu Xu and posted to the
> IETF repository.
>
> Name: draft-xu-lsr-fare
> Revision: 00
> Title:Fully Adaptive Routing Ethernet
> Date: 2023-11-22
> Group:Individual Submission
> Pages:7
> URL: https://www.ietf.org/archive/id/draft-xu-lsr-fare-00.txt
> Status: https://datatracker.ietf.org/doc/draft-xu-lsr-fare/
> HTMLized: https://datatracker.ietf.org/doc/html/draft-xu-lsr-fare
>
>
> Abstract:
>
>Large language models (LLMs) like ChatGPT have become increasingly
>popular in recent years due to their impressive performance in
>various natural language processing tasks. These models are built by
>training deep neural networks on massive amounts of text data, often
>consisting of billions or even trillions of parameters. However, the
>training process for these models can be extremely resource-
>intensive, requiring the deployment of thousands or even tens of
>thousands of GPUs in a single AI training cluster. Therefore, three-
>stage or even five-stage CLOS networks are commonly adopted for AI
>networks. The non-blocking nature of the network become increasingly
>critical for large-scale AI models. Therefore, adaptive routing is
>necessary to dynamically load balance traffic to the same destination
>over multiple ECMP paths, based on network capacity and even
>congestion information along those paths.
>
>
>
> The IETF Secretariat
>
>
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