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GSE architecture for AIDC
draft-zhuang-rtgwg-aidc-gse-architecture-00

Document Type Active Internet-Draft (individual)
Authors Rui Zhuang , Zheng Zhang
Last updated 2026-06-24
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draft-zhuang-rtgwg-aidc-gse-architecture-00
RTGWG                                                          R. Zhuang
Internet-Draft                                              China Mobile
Intended status: Informational                             Z. Zhang, Ed.
Expires: 26 December 2026                                ZTE Corporation
                                                            24 June 2026

                       GSE architecture for AIDC
              draft-zhuang-rtgwg-aidc-gse-architecture-00

Abstract

   This document introduces a Global Scheduling Ethernet (GSE)
   architecture for data centers used for AI computing.  This
   architecture can minimize the probability of packet forwarding
   congestion in the network and improve the efficiency of packet
   interaction.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on 26 December 2026.

Copyright Notice

   Copyright (c) 2026 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (https://trustee.ietf.org/
   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
   and restrictions with respect to this document.  Code Components
   extracted from this document must include Revised BSD License text as
   described in Section 4.e of the Trust Legal Provisions and are
   provided without warranty as described in the Revised BSD License.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   2
   2.  GSE Architecture  . . . . . . . . . . . . . . . . . . . . . .   2
   3.  GSE deployment scenarios  . . . . . . . . . . . . . . . . . .   4
     3.1.  GSE Scenario 1  . . . . . . . . . . . . . . . . . . . . .   4
     3.2.  GSE Scenario 2  . . . . . . . . . . . . . . . . . . . . .   5
     3.3.  GSE summary . . . . . . . . . . . . . . . . . . . . . . .   7
   4.  GSE header  . . . . . . . . . . . . . . . . . . . . . . . . .   7
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .   8
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   8
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .   8
     7.2.  Informative References  . . . . . . . . . . . . . . . . .   8
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   The development of Artificial Intelligence (AI) and Machine Learning
   (ML) has brought about a transformation in data center development.
   Due to the data-intensive nature of large language model (LLM)
   computations, AI tasks often generate large amounts of traffic.  If
   the link bandwidth is insufficient, it can lead to packet loss or
   significant latency.  AI computation has very high reliability
   requirements and extremely low tolerance for packet loss and latency.
   Network congestion that causes packet loss or excessive latency will
   significantly impact the computational efficiency of AI tasks.

   There are many implementations in the industry to reduce packet loss
   and latency.  This document introduces an implementation architecture
   called GSE for reference.

1.1.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in [RFC2119].

2.  GSE Architecture

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                        +------------+
                        | Controller |                    Control Layer
                        +------------+
   --------------------------------------------------------------------

                                                         Network Layer
           +-------+    +-------+           +-------+
           | Spine |    | Spine |  ......   | Spine |     Layer2
           +-------+    +-------+           +-------+

           +-------+    +-------+           +-------+
           | Spine |    | Spine |  ......   | Spine |     Layer1
           +-------+    +-------+           +-------+

       +------+   +------+   +------+   +------+        +------+
       | Leaf |   | Leaf |   | Leaf |   | Leaf | ...... | Leaf |
       +------+   +------+   +------+   +------+        +------+
   --------------------------------------------------------------------

                                                      Computation Layer
   +--------+  +--------+  +--------+  +--------+        +--------+
   | Server |  | Server |  | Server |  | Server | ...... | Server |
   +--------+  +--------+  +--------+  +--------+        +--------+

                                  Figure 1

   Figure 1 shows a common data center architecture for AI computing,
   divided into three layers: control layer, network layer, and
   computation layer.

   *  The computation layer consists of servers used for AI computing,
      including GPUs and NICs.

   *  The network layer uses a common Clos/Fat Tree topology as an
      example, while other topologies can also be used in practice.  In
      a 3-layer Clos topology, it consists of Leaf switches connected to
      the servers and Layer 1 and Layer 2 Spine switches.

   *  The control layer consists of centralized or distributed
      controllers.

   This document mainly focuses on implementation methods for the
   network layer.  Notably, cross-layer collaboration between the
   network layer and the computation layer is also required.

   To meet the stringent packet loss and latency requirements for AI
   computing, the following implementation mechanisms can be used at the
   network layer:

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   *  Credit-based authorization mechanism: The main idea is to use
      credit-based authorization to control data transmission and reduce
      congestion probability.  Before packet transmission, the sender
      initiates an authorization request to the receiver to ensure that
      the receiver has sufficient bandwidth to receive packets, thereby
      avoiding packet loss caused by last-hop congestion.

   *  Packet aggregation mechanism: The main idea is to aggregate
      packets into uniform-sized segments, which is more conducive to
      packet forwarding and reception control.

   *  Improved ECMP mechanism: This mechanism not only distributes
      traffic evenly across ECMP links to avoid congestion, but also
      ensures in-order packet arrival at the destination, thereby
      reducing the buffering and processing overhead at the receiver.

   Additionally, technologies such as PFC (Priority-based Flow Control,
   IEEE802.1Qbb) and ECN (Explicit Congestion Notification, [RFC3168])
   are also deployed to further reduce congestion-related packet loss.

3.  GSE deployment scenarios

3.1.  GSE Scenario 1

              +----------+                        +----------+
              |  Spine1  |                        |  Spine2  |
              +--+-+-+-+-+                        +--+-+-+-+-+
                 | | | |                             | | | |
               +-------------------------------------+ | | |
               | | | | |    +--------------------------+ | |
               | | | | |    |                   +--------+ |
               | | | | |    |                   |          |
               | | | | +--------------------------------------+
               | | | +-----------------------+  |          |  |
             +---+ +------+ |                |  |          |  |
             | |          | |                |  |          |  |
        +----+-+--+    +--+-+----+        +--+--+---+    +-+--+----+
        |  Leaf1  |    |  Leaf2  |        |  Leaf3  |    |  Leaf4  |
        +-+-----+-+    +-+-----+-+        +-+-----+-+    +-+-----+-+
          |     |        |     |            |     |        |     |
          | ..  |        | ... |            | ... |        | ... |
          |     |        |     |            |     |        |     |
        +-+-----+-+    +-+-----+-+        +-+-----+-+    +-+-----+-+
        |N1|N2|...|    |N9|N10|..|        |N17|N18|.|    |N25|N26|.|
        +---------+    +---------+        +---------+    +---------+
          Server1        Server2            Server3        Server4

                                  Figure 2

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   Each server include GPUs, NICs, etc.  As shown in Figure 2, NIC1
   connects to Leaf1, and NIC20 connects to Leaf3.  Take the scenario
   where GPU1 sends AI computing traffic to GPU20 as an example: Before
   sending the traffic, NIC1, to which GPU1 is connected, initiates an
   authorization request to NIC20, to which GPU20 is connected.  Both
   the request and response messages are encapsulated in a specific
   message to ensure identification and forwarding by switches.  When
   NIC20 confirms that traffic transmission is possible, it sends a
   negotiation response to NIC1.  NIC1 only begins traffic sending after
   receiving the authorization response.

   This specific message (including negotiation request and negotiation
   response) is generated and sent by hardware such as chips.  Its outer
   addressing can adopt an encapsulation similar to the GSE header
   defined in this document.  This specific negotiation message includes
   information such as the required bandwidth, which is not defined in
   this draft.  This negotiation mechanism applies bidirectionally.  For
   example, the same workflow is followed when GPUs on Server2 or
   Server3 send traffic to GPU1 on Server1.

   This negotiation mechanism requires a link between the NIC and the
   Leaf switch, which can be identified by the address of GPU/NIC plus
   the interface index connected to the Leaf switch.  For NICs
   supporting the credit authorization mechanism, the NIC obtains the
   port ID from its upstream Leaf switch, and initiates credit
   authorization requests and responses based on this set of
   identification information.  Information exchange between the NIC and
   the Leaf switch can be implemented via private ARP messages or
   extensions such as LLDP, which are not defined in this document.
   This GPU/NIC address and associated port information can be
   advertised via control plane routing protocols, learned through
   interactions between the Leaf and Spine switches.

   If the NIC does not support the authorization mechanism, this process
   can also be done by the Leaf switch connected to the NIC.

3.2.  GSE Scenario 2

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      +--------------------------------------------------------+
      |                                            ...  PodM   |
      |                                                        |
      |   +----------+  +----------+         +----------+      |
      |   |  Core1   |  |  Core2   |  ...    |  CoreZ   |      |
      |   +--+-------+  ++---------+         +----------+      |
      |      |           |       ......                        |
      |      |      +----+                                     |
      |      |      |                                          |
      |   +--+------++  +----------+         +----------+      |
      +-- |  SSpine1 |  |  SSpine2 |   ...   | SSpineN  | -----+
          +----------+  +----------+         +----------+

              +----------+                     +----------+
              |  Spine1  |                     |  Spine2  |
              +----------+                     +----------+

        +----+-+--+    +--+-+----+        +--+--+---+    +-+--+----+
        |  Leaf1  |    |  Leaf2  |        |  Leaf3  |    |  Leaf4  |
        +-+-----+-+    +-+-----+-+        +-+-----+-+    +-+-----+-+
          |
        +-+-----+-+    +-+-----+-+        +-+-----+-+    +-+-----+-+
        |N1|N2|...|    |N9|N10|..|        |N17|N18|.|    |N25|N26|.|
        +---------+    +---------+        +---------+    +---------+
              Server1        Server2            Server3        Server4

                                  Figure 3

   Figure 1 only shows a portion of a single PoD.  Typical data centers
   used for AI computing are much larger and require more connections to
   other PoDs.  Figure 3 provides an example where not all connections
   are displayed due to the complexity of the wiring.  Each PoD's SSpine
   switch is connected to other PoDs' SSpine switches via a Core switch.
   It is difficult to ensure that traffic flows from one PoD's Leaf
   switch to another PoD's Leaf switch without congestion throughout the
   entire forwarding process.  However, within a single PoD, a method
   similar to that in Scenario 1 can be used, employing GSE to ensure
   low-latency, congestion-free forwarding of traffic from the Leaf
   switch to the Core switch.

   Before forwarding traffic from N1, Leaf1 sends a negotiation message
   to the SSpine1 switch, specifying the link between SSpine1 and Core1.
   Leaf1 will only begin forwarding traffic from N1 if the bandwidth
   between SSpine1 and Core1 is sufficient, i.e., if the negotiation is
   successful.  If the link bandwidth between SSpine1 and Core1 is
   insufficient, Leaf1 can send another negotiation message to the
   SSpine1 switch, specifying the link between SSpine1 and Core2.
   Again, Leaf1 will only begin forwarding traffic from N1 if the

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   negotiation is successful.  This ensures that unless a link failure
   occurs, there will be no packet loss before the traffic reaches
   Core1.

3.3.  GSE summary

   The requirements for the two scenarios above are similar; both
   require carrying the corresponding port information when announcing
   routes (routes from the NIC/GPU and routes obtained from other PoDs).
   Therefore, the port ID information used for authorization can be
   advertised along with the route; for the advertising method, refer to
   [I-D.zhang-idr-portid-ec].  Based on the information, certain
   existing implementations support pre-transmission negotiation to
   ensure sufficient bandwidth at the egress point before sending
   traffic.

   After traffic transmission begins, data packets are aggregated into
   uniform-sized segments, and sequence numbers are added to these
   packets based on the segments they belong to.  This ensures that even
   if a link fails or congestion occurs, data packets passing through
   different paths can be reordered based on sequence numbers.  During
   the transmission of the same segment, in order to utilize the same
   path on the ECMP links as much as possible to reduce the buffering
   and processing pressure on packet reassembly, an entropy value is
   needed to guarantee the stability of path selection.  In some
   implementations, the source and destination queue identifiers, such
   as QP, can be used directly as entropy.  Although this mechanism
   reduces the probability of congestion, network congestion can still
   occur.  In such cases, other idle or light load ECMP links can be
   used to transmit segments.  Simultaneously, mechanisms such as PFC
   and ECN can be also used to adjust the traffic transmission rate,
   thereby further reducing the probability of congestion.

   Such a message forwarding mechanism is difficult to implement using
   traditional IP-based forwarding, so additional definitions may be
   required.  These defined fields can be identified and processed by
   GSE header encapsulation.

4.  GSE header

    +------------------------------------------------------------------+
    |  Destination | port-ID | Priority | Entropy | Seq | ......
    +------------------------------------------------------------------+

                                  Figure 4

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   Figure 4 shows a GSE packet header example for reference.  It can be
   recognized and forwarded by the network layer, one implementation
   uses a new type Ethernet encapsulation.

   *  Destination: The IP address or address value of the GPU/NIC or
      switch;

   *  port-ID: Port-ID used for authorization;

   *  Priority: Traffic transmission priority, similar to DSCP.

   *  Entropy: Values used for traffic load balancing.

   *  Seq: The sequence number of the data packet is used for reassembly
      in case of out-of-order delivery.

5.  IANA Considerations

   This document includes no request to IANA.

6.  Security Considerations

   This draft provides an implementation reference.  Implementing this
   scheme will introduce new packet identification and forwarding
   processes, impacting the implementation of switches and NICs.
   Inappropriate implementation and deployment may lead to packet
   forgery attacks.

7.  References

7.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/info/rfc2119>.

7.2.  Informative References

   [I-D.zhang-idr-portid-ec]
              Zhang, J., Zhuang, R., Zhang, Z., and D. Yuan, "BGP PORT
              EC for AIDC", Work in Progress, Internet-Draft, draft-
              zhang-idr-portid-ec-01, 15 March 2026,
              <https://datatracker.ietf.org/doc/html/draft-zhang-idr-
              portid-ec-01>.

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   [RFC3168]  Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
              of Explicit Congestion Notification (ECN) to IP",
              RFC 3168, DOI 10.17487/RFC3168, September 2001,
              <https://www.rfc-editor.org/info/rfc3168>.

Authors' Addresses

   Rui Zhuang
   China Mobile
   China
   Email: zhuangruiyjy@chinamobile.com

   Zheng Zhang (editor)
   ZTE Corporation
   China
   Email: zhang.zheng@zte.com.cn

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