<p>NVIDIA has released a video that offers the first public look at Eos, its latest data-center-scale supercomputer.</p>
<p>An extremely large-scale <a href="https://www.nvidia.com/en-us/data-center/dgx-superpod/">NVIDIA DGX SuperPOD</a>, Eos is where NVIDIA developers create their AI breakthroughs using accelerated computing infrastructure and fully optimized software.</p>
<p>Eos is built with 576 <a href="https://www.nvidia.com/en-us/data-center/dgx-h100/">NVIDIA DGX H100</a> systems, <a href="https://www.nvidia.com/en-us/networking/quantum2/">NVIDIA Quantum-2 InfiniBand networking</a> and software, providing a total of 18.4 exaflops of FP8 AI performance.</p>
<p>Revealed in November at the Supercomputing 2023 trade show, Eos — named for the Greek goddess said to open the gates of dawn each day — reflects NVIDIA’s commitment to advancing AI technology.</p>
<p>Each DGX H100 system is equipped with eight <a href="https://www.nvidia.com/en-us/data-center/h100/">NVIDIA H100 Tensor Core GPUs</a>. Eos features a total of 4,608 H100 GPUs.</p>
<p>As a result, Eos can handle the largest AI workloads to train <a href="https://blogs.nvidia.com/blog/kt-large-language-models/">large language models</a>, recommender systems, quantum simulations and more.</p>
<p>It’s a showcase of what NVIDIA’s technologies can do, when working at scale.</p>
<p>Eos is arriving at the perfect time. People are changing the world with <a href="https://www.nvidia.com/en-us/glossary/generative-ai/">generative AI</a>, from drug discovery to chatbots to autonomous machines and beyond.</p>
<p>To achieve these breakthroughs, they need more than AI expertise and development skills. They need an AI factory — a purpose-built AI engine that’s always available and can help ramp their capacity to build AI models at scale</p>
<p>Eos is r<a href="https://www.top500.org/lists/top500/2023/11/">anked No. 9 in the TOP500</a> list of the world’s fastest supercomputers.</p>
<p>It includes NVIDIA’s advanced accelerated computing and networking alongside sophisticated software offerings such as <a href="https://www.nvidia.com/en-us/data-center/base-command/">NVIDIA Base Command</a> and <a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/">NVIDIA AI Enterprise</a>.</p>
<p>Eos’s architecture is optimized for AI workloads demanding ultra-low-latency and high-throughput interconnectivity across a large cluster of accelerated computing nodes, making it an ideal solution for enterprises looking to scale their AI capabilities.</p>
<p>Based on NVIDIA Quantum-2 InfiniBand with In-Network Computing technology, its network architecture supports data transfer speeds of up to 400Gb/s, facilitating the rapid movement of large datasets essential for training complex AI models.</p>
<p>At the heart of Eos lies the groundbreaking DGX SuperPOD architecture powered by NVIDIA’s DGX H100 systems.</p>
<p>The architecture is built to provide the AI and computing fields with tightly integrated full-stack systems capable of computing at an enormous scale.</p>
<p><iframe width="560" height="315" src="https://www.youtube.com/embed/J8-CgG5ewJQ?si=Aooz5uwQcHCxxApq" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe></p>

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