Outlook into NVIDIA's Fastest AI Supercomputer: DGX H200

Nvidia CEO Jensen Huang personally delivered the world’s fastest AI supercomputer, the DGX H200 server with H200 Tensor Core GPU to OpenAI. The history of collaboration between Nvidia and OpenAI dates back to 2016 when Nvidia handed over the first AI supercomputer to OpenAI. This time Nvidia has brought DGX H200 on board which is designed to be faster and more efficient than its predecessors.

What are the key features of the AI supercomputer DGX H200?

The DGX H200 is Nvidia’s latest and most powerful  AI supercomputer system, that is designed to accelerate AI research and development. Some of its key features are:

• It is powered by Nvidia’s new H200 Tensor Core GPU. The H200 has 141GB of HBM3e memory running at 4.8TB/s. It makes it the GPU with the highest memory capacity.
• The DGX H200 is claimed to be the “world’s most powerful GPU for supercharging AI workloads. It offers up to 40% better performance on larger language models as compared to the previous generation.
• The system is 50% more power efficient than the previous DGX H100 model allowing for more compute power while consuming less energy.
• The DGX H200 is designed as an enterprise-grade server system for organizations working on large-scale AI projects that require immense computing power.
• In contrast, the previous generation DGX-2 server used 16 Volta-based V100 GPUs, while the DGX GH200 connects 32 Hopper Superchips with 256 H100 GPUs for even greater performance.

What are the use cases of DGX H200?

The DGX H200 is specifically designed for accelerating generative AI tasks and is twice as fast as its predecessor. It is responsible for handling terabyte-class models for massive recommender systems, generative AI, and graph analytics, offering 19.5 TB of shared memory with linear scalability for massive AI models.

Conclusion

Nvidia’s AI supercomputer DGX H200 server represents a significant advancement in GPU-based computing, offering superior performance, efficiency, memory capacity, and bandwidth compared to other Nvidia servers like DGX H100 and DGX GH200.