Summary: NVIDIA Announces DGX GH200 AI Supercomputer

Fully Integrated and Purpose-Built for Giant Models

DGX GH200 supercomputers include NVIDIA software to provide a turnkey, full-stack solution for the largest AI and data analytics workloads.

“DGX GH200 AI supercomputers integrate NVIDIA’s most advanced accelerated computing and networking technologies to expand the frontier of AI.”

NVIDIA NVLink Technology Expands AI at Scale

GH200 superchips eliminate the need for a traditional CPU-to-GPU PCIe connection by combining an Arm-based NVIDIA Grace™ CPU with an NVIDIA H100 Tensor Core GPU in the same package, using NVIDIA NVLink-C2C chip interconnects.

“The potential for DGX GH200 to work with terabyte-sized datasets would allow developers to conduct advanced research at a larger scale and accelerated speeds.”

New NVIDIA Helios Supercomputer to Advance Research and Development

NVIDIA is building its own DGX GH200-based AI supercomputer to power the work of its researchers and development teams.

The DGX GH200 architecture provides 48x more NVLink bandwidth than the previous generation, delivering the power of a massive AI supercomputer with the simplicity of programming a single GPU.

New Class of AI Supercomputer Connects 256 Grace Hopper Superchips Into Massive, 1-Exaflop, 144TB GPU for Giant Models Powering Generative AI, Recommender Systems, Data Processing

COMPUTEX—NVIDIA today announced a new class of large-memory AI supercomputer — an NVIDIA DGX ™ supercomputer powered by NVIDIA ® GH200 Grace Hopper Superchips and the NVIDIA NVLink ® Switch System — created to enable the development of giant, next-generation models for generative AI language applications, recommender systems and data analytics workloads.

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NVIDIA Announces DGX GH200 AI Supercomputer

NVIDIA today announced a new class of large-memory AI supercomputer — an NVIDIA DGX™ supercomputer powered by NVIDIA® GH200 Grace Hopper Superchips and the NVIDIA NVLink® Switch System — created to enable the development of giant, next-generation models for generative AI language applications, recommender systems and data analytics workloads.

Read the complete article at: nvidianews.nvidia.com