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--- network_stuff:machine_learning:networking:ai:networking [2026/02/01 15:25] – jotasandoku
+++ network_stuff:machine_learning:networking:ai:networking [2026/02/01 17:37] (current) – jotasandoku
@@ Line 55: / Line 55: @@
 [[https://camarreal.dedyn.io/doku.php?id=network_stuff:machine_learning:networking:ai:infiniband]]
-=== ROCEV2 ===
+==== ROCEV2 =====
 [[ https://netdevconf.info/0x19/docs/netdev-0x19-paper18-talk-slides/netdev-0x19-AI-networking-RoCE-and-netdev.pdf ]]
 \\
@@ Line 67: / Line 67: @@
   * **Compatibility with AI Workloads**: Like InfiniBand, **RoCE** supports high-speed, low-latency, and lossless communication, making it ideal for distributed AI workloads such as training deep learning models across multiple GPUs or nodes.
   * __QP (Queue Pair)__: is a fundamental concept representing an RDMA connection. It consists of a send queue and a receive queue.
-  * __BTH Base Transport Header__: is a key component within RoCEv2 packets, carrying essential information like:#
+  * __InfiniBand Base Transport Header (IB BTH)__: is a key component within RoCEv2 packets, carrying essential information like. It is the same as in Infiniband (but now is inside IP-UDP:#
     * Packet Sequence Number (PSN), QP Number, and acknowledgment request bits.
+    * **Version:** Indicates the version of the InfiniBand protocol being used.
+    * **Reserved:** A field reserved for future use or alignment purposes.
+    * **Packet Length:** Specifies the total length of the packet in bytes.
+    * **Class Version:** Indicates the class and version of the transport protocol.
+    * **Operation (OpCode): Defines the type of operation being performed (e.g., WRITE, READ, SEND, RECEIVE).**
+    * **Transaction ID:** A unique identifier for tracking requests and responses.
+    * **Destination Queue Pair (QP):** Identifies the destination queue used for receiving the packet.
 \\
 Packet structure:
@@ Line 99: / Line 107: @@
-=== Ultra Ethernet === is an evolving concept that builds on **RoCE** to create even more robust, low-latency, and lossless Ethernet environments. Companies like **Nvidia** and **Arista** are leading the charge with **Ultra Ethernet** to create an optimized Ethernet fabric for AI workloads, where predictable, lossless communication is key.
+===**Congestion control** in ROCEV2 ===
+  * DCQCN
+    * PFC
+    * ECN
+==== Ultra Ethernet ==== is an evolving concept that builds on **RoCE** to create even more robust, low-latency, and lossless Ethernet environments. Companies like **Nvidia** and **Arista** are leading the charge with **Ultra Ethernet** to create an optimized Ethernet fabric for AI workloads, where predictable, lossless communication is key.
 **Link:** [[https://ultraethernet.org/ultra-ethernet-specification-update/|Ultra Ethernet Specification]]

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