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NVIDIA’s Powerhouse: Top 10 Supercomputer

NVIDIA unveiled a video that gives the public its first look at Eos, its newest data-center-scale supercomputer, giving a glimpse at the architecture that powers advanced AI factories. Here at Eos, an exceptionally large-scale NVIDIA DGX SuperPOD, NVIDIA developers use accelerated processing infrastructure and fully optimized software to produce AI breakthroughs.

EOS boasts a whopping 18.4 exaflops of FP8 AI performance, thanks to its 576 NVIDIA DGX H100 workstations, NVIDIA Quantum-2 InfiniBand networking, and software. A different Eos DGX SuperPOD with 10,752 NVIDIA H100 GPUs was utilized for MLPerf training in November, and this system is its sister. Eos, unveiled in November at the Supercomputing 2023 trade exhibition, represents NVIDIA’s dedication to developing artificial intelligence. The name is derived from the Greek goddess who is said to open the gates of dawn daily.There are a total of eight GPUs—NVIDIA H100 Tensor Cores—inside every DGX H100 system. There are 4,608 H100 GPUs in all of Eos.

This means that Eos is capable of training large language models, recommender systems, quantum simulations, and other AI tasks. It exemplifies the capabilities of NVIDIA’s technologies when applied in a large-scale setting.

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Finally, Eos has arrived just in time. From drug research and chatbots to autonomous machines and beyond, generative AI is altering the world. Beyond knowledge of AI and programming abilities, they will require other resources to accomplish these innovations. To increase their ability to construct AI models on a large scale, they require an AI factory, which is an AI engine designed specifically for this purpose and is available 24/7.

With it, you get cutting-edge networking and processing capabilities from NVIDIA, as well as high-end applications from NVIDIA like Base Command and AI Enterprise.Eos is a great option for businesses that want to expand their AI capabilities because of its architecture, which is designed for AI workloads that require high-throughput, low-latency communication across a large cluster of accelerated compute nodes. Supporting data transfer speeds of up to 400Gb/s, its network design is based on NVIDIA Quantum-2 InfiniBand with In-Network Computing technology. This allows for the quick movement of massive datasets, which are crucial for training sophisticated AI models.

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With this design, the artificial intelligence and computer science communities will have access to fully integrated systems that can handle massive amounts of data. Enterprises and developers around the world are rushing to tap into AI’s potential, and Eos is a key resource that might speed up the process of creating AI-infused apps that power all businesses.

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