02/27/2024 | Press release | Distributed by Public on 02/27/2024 10:19
The spirit of Grace Hopper will live on at NVIDIA GTC.
Accelerated systems using powerful processors - named in honor of the pioneer of software programming - will be on display at the global AI conference running March 18-21, ready to take computing to the next level.
System makers will show more than 500 servers in multiple configurations across 18 racks, all packing NVIDIA GH200 Grace Hopper Superchips. They'll form the largest display at NVIDIA's booth in the San Jose Convention Center, filling the MGX Pavilion.
NVIDIA MGX is a blueprint for building accelerated servers with any combination of GPUs, CPUs and data processing units (DPUs) for a wide range of AI, high performance computing and NVIDIA Omniverse applications. It's a modular reference architecture for use across multiple product generations and workloads.
GTC attendees can get an up-close look at MGX models tailored for enterprise, cloud and telco-edge uses, such as generative AI inference, recommenders and data analytics.
The pavilion will showcase accelerated systems packing single and dual GH200 Superchips in 1U and 2U chassis, linked via NVIDIA BlueField-3 DPUs and NVIDIA Quantum-2 400Gb/s InfiniBand networks over LinkX cables and transceivers.
The systems support industry standards for 19- and 21-inch rack enclosures, and many provide E1.S bays for nonvolatile storage.
Here's a sampler of MGX systems now available:
The new servers are in addition to three accelerated systems using MGX announced at COMPUTEX last May - Supermicro's ARS-221GL-NR using the Grace CPU and QCT's QuantaGrid S74G-2U and S74GM-2U powered by the GH200.
System builders are adopting the hybrid processor because it packs a punch.
GH200 Superchips combine a high-performance, power-efficient Grace CPU with a muscular NVIDIA H100 GPU. They share hundreds of gigabytes of memory over a fast NVIDIA NVLink-C2C interconnect.
The result is a processor and memory complex well-suited to take on today's most demanding jobs, such as running large language models. They have the memory and speed needed to link generative AI models to data sources that can improve their accuracy using retrieval-augmented generation, aka RAG.
In addition, the GH200 Superchip delivers greater efficiency and up to 4x more performance than using the H100 GPU with traditional CPUs for tasks like making recommendations for online shopping or media streaming.
In its debut on the MLPerf industry benchmarks last November, GH200 systems ran all data center inference tests, extending the already leading performance of H100 GPUs.
In all these ways, GH200 systems are taking to new heights a computing revolution their namesake helped start on the first mainframe computers more than seven decades ago.
Register for NVIDIA GTC, the conference for the era of AI, running March 18-21 at the San Jose Convention Center and virtually.
And get the 30,000-foot view from NVIDIA CEO and founder Jensen Huang in his GTC keynote.