Converged scale-up and scale-out networks

A system comprising a converged scale-up and scale-out network, comprising:

• a centralized controller comprising one or more processors operable to:
• register each compute node of the backend network, each compute node comprising one or more Artificial Intelligence (AI) accelerators, and wherein each compute node is part of one of a plurality of distinct pods of the backend network;
• register each scale-up switch of the backend network, wherein each scale-up switch is specific to a particular one of the plurality of pods and connects a plurality of compute nodes within its particular pod to each other;
• register each scale-out switch of the backend network, wherein each scale-out switch is specific to a particular one of the plurality of pods and connects a plurality of compute nodes within its particular pod to the scale-out network outside the pod;
• and
• dynamically determine, for a particular AI task, (1) whether to provide scale-up or scale-out resources for the task and (2) based on the determination, a set of compute nodes of the backend network to allocate to the task;
• a control plane comprising one or more processors coupled to a memory to generate a data plane defining a data path for the allocated set of compute nodes;
• and
• the data plane, comprising (1) the allocated set of compute nodes (2) one or more corresponding scale-up switches and (3) one or more corresponding scale-out switches, the data plane configured to perform the particular AI task,
• wherein the one or more processors of the centralized controller are further configured to configure a unified address for each of the compute nodes,
• wherein the unified address comprises any of:
• a subnet address identifying a scale-out address, wherein the subnet address is the same for each compute node in a particular pod;
• and
• a host address identifying a scale-up address, wherein the host address is different for each compute node in the particular pod.