Nvidia unveils new GPU-based platform to fuel generative AI performance

Nvidia has announced a new AI computing platform called Nvidia HGX H200, a turbocharged version of the company’s Nvidia Hopper architecture powered by its latest GPU offering, the Nvidia H200 Tensor Core.

The company also is teaming up with HPE to offer a supercomputing system, built on the Nvidia Grace Hopper GH200 Superchips, specifically designed for generative AI training.

A surge in enterprise interest in AI has fueled demand for Nvidia GPUs to handle generative AI and high-performance computing workloads. Its latest GPU, the Nvidia H200, is the first  to offer HBM3e, high bandwidth memory that is 50% faster than current HBM3, allowing for the delivery of 141GB of memory at 4.8 terabytes per second, providing double the capacity and 2.4 times more bandwidth than its predecessor, the Nvidia A100.

Nvidia unveiled the first HBM3e processor, the GH200 Grace Hopper Superchip platform, in August “to meet [the] surging demand for generative AI,” founder and CEO of Nvidia, Jensen Huang, said at the time. 

The introduction of the Nvidia H200 will lead to further performance leaps, the company said in a statement, adding that when compared to its H100 offering, the new architecture will nearly double the inference speed on Meta’s 70 billion-parameter LLM Llama-2. Parameters relate to how neural networks are configured.

“To create intelligence with generative AI and HPC applications, vast amounts of data must be efficiently processed at high speed using large, fast GPU memory,” said Ian Buck, vice president of hyperscale and HPC at Nvidia in a statement accompanying the announcement. “With Nvidia H200, the industry’s leading end-to-end AI supercomputing platform just got faster to solve some of the world’s most important challenges.”