Nvidia on Thursday published a video that gives the first public glimpse into the architecture of Eos, its newest enterprise-oriented supercomputer designed for advanced AI development at the datacenter scale, and the company’s fastest AI supercomputer.
The Eos machine, currently being used by Nvidia itself, is ranked as the world’s No. 9 highest performing supercomputer in the latest Top 500 list, which is measured in FP64; in pure AI tasks, it’s likely among the fastest. Meanwhile, its blueprint can be used to build enterprise-oriented supercomputers for other companies too.
“Every day EOS rises to meet the challenges of thousands of Nvidia’s in-house developers doing AI research, helping them solve the previously unsolvable,” Nvidia stated in the video.
Nvidia’s Eos is equipped with 576 DGX H100 systems, each containing eight Nvidia H100 GPUs for artificial intelligence (AI) and high-performance computing (HPC) workloads. In total, the system packs 1,152 Intel Xeon Platinum 8480C (with 56 cores per CPU) processors as well as 4,608 H100 GPUs, enabling Eos to achieve an impressive Rmax 121.4 FP64 PetaFLOPS as well as 18.4 FP8 ExaFLOPS performance for HPC and AI, respectively.
The design of Eos (which relies on the DGX SuperPOD architecture) is purpose built for AI workloads as well as scalability, so it uses Nvidia’s Mellanox Quantum-2 InfiniBand with In-Network Computing technology that features data transfer speeds of up to 400 Gb/s, which is crucial for training large AI models effectively as well as scaling out.
In addition to powerful hardware, Nvidia’s Eos also comes with potent software, again, purpose-built for AI development and deployment, the company says. As a result, Nvidia’s Eos can address a variety of applications, from a ChatGPT-like generative AI to AI factory.
“Eos has an integrated software stack that includes AI development and deployment software, [including] orchestration and cluster management, accelerated compute storage and network libraries, and an operating system optimized for AI workloads,” Nvidia said in the video. “Eos — built from the knowledge gained with prior Nvidia DGX supercomputers such as Saturn 5 and Selene — is the latest example of Nvidia AI expertise in action. […] By creating an AI factory like Eos, enterprises can take on their most demanding projects and achieve their AI aspirations today and into the future.”
We don’t know how much Eos costs, and it doesn’t help that pricing of Nvidia’s DGX H100 systems is confidential and dependent on many factors, such as volumes. Meanwhile, considering the fact that each Nvidia H100 can cost $30,000 — $40,000 depending on the volume, so one can start thinking about how high the numbers we get here.
