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How Meta trains large language models at scale

Engineering at Meta

Data center deployment Once we’ve chosen a GPU and system, the task of placing them in a data center for optimal usage of resources (power, cooling, networking, etc.) There are two leading choices in the industry that fit these requirements: RoCE and InfiniBand fabrics. Both of these options had tradeoffs.

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A RoCE network for distributed AI training at scale

Engineering at Meta

Distributed training, in particular, imposes the most significant strain on data center networking infrastructure. Constructing a reliable, high-performance network infrastructure capable of accommodating this burgeoning demand necessitates a reevaluation of data center network design.

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Building Meta’s GenAI Infrastructure

Engineering at Meta

Today, we’re sharing details on two versions of our 24,576-GPU data center scale cluster at Meta. Custom designing much of our own hardware, software, and network fabrics allows us to optimize the end-to-end experience for our AI researchers while ensuring our data centers operate efficiently.

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Top Tips for Debugging and Optimizing NVIDIA Networking Performance

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In today’s high-speed networking world, optimizing and troubleshooting performance is crucial, especially with high-performance equipment like NVIDIA Infiniband switches. Whether you’re a data center admin or network engineer, mastering effective techniques is key.