Remove Bandwidth Remove Ethernet Remove Infiniband
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HN755: Optimizing Ethernet to Meet AI Infrastructure Demands

Packet Pushers

Ethernet competes with InfiniBand as a network fabric for AI workloads such as model training. And while Ethernet has kept up with increasing demands to support greater bandwidth and throughput, it was. Read more » Ethernet competes with InfiniBand as a network fabric for AI workloads such as model training.

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NAN071: Understanding the Infrastructure Requirements for AI Workloads (Sponsored)

Packet Pushers

We discuss key considerations including bandwidth, the substantial power and cooling requirements of AI infrastructure, and GPUs. We also talk about InfiniBand and Ethernet as network fabrics for AI workloads, cabling considerations, and more. This is a sponsored episode. This is a sponsored episode. Read more »

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A RoCE network for distributed AI training at scale

Engineering at Meta

Our paper, “ RDMA over Ethernet for Distributed AI Training at Meta Scale ,” provides the details on how we design, implement, and operate one of the world’s largest AI networks at scale. We opted for RDMA Over Converged Ethernet version 2 (RoCEv2) as the inter-node communication transport for the majority of our AI capacity.

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Building Meta’s GenAI Infrastructure

Engineering at Meta

With this in mind, we built one cluster with a remote direct memory access (RDMA) over converged Ethernet (RoCE) network fabric solution based on the Arista 7800 with Wedge400 and Minipack2 OCP rack switches. The other cluster features an NVIDIA Quantum2 InfiniBand fabric. Both of these solutions interconnect 400 Gbps endpoints.