NVIDIA announced the HGX H200 in November 2023. It is the latest addition to the company’s line of high-performance computing (HPC) systems, and it is designed specifically for training generative AI models.
Generative AI models are a type of AI that can generate new content, such as text, images, and code. They are used in a wide range of applications, including natural language processing, computer vision, and robotics.
The NVIDIA HGX H200 is the most powerful chip available for training generative AI models. It is expected to be used by a wide range of customers, including research labs, startups, and large enterprises.
Here are some of the key features of the NVIDIA HGX H200:
- Up to 141 GB of HBM3 memory
- Up to 32 petaflops of FP8 deep learning compute
- Up to 1.1 TB of aggregate high-bandwidth memory
The NVIDIA HGX H200 is expected to be available in the second quarter of 2024.
Key Benefits of the NVIDIA HGX H200
The NVIDIA HGX H200 offers a number of benefits over previous generations of chips, including:
- Significantly improved performance: The HGX H200 delivers up to 2.5x the performance of the previous generation, making it the fastest chip available for training generative AI models.
- Improved memory bandwidth: The HGX H200 features a new memory architecture that delivers up to 2x the bandwidth of the previous generation. This means that the chip can more quickly access the data it needs to train AI models.
- Improved AI acceleration: The HGX H200 features a new AI accelerator that delivers up to 4x the performance of the previous generation. This means that the chip can more efficiently train AI models.
Impact on Generative AI Development
The NVIDIA HGX H200 is expected to have a significant impact on the development of generative AI. The chip’s improved performance, memory bandwidth, and AI acceleration will enable developers to train larger and more complex AI models. This will lead to the development of new and innovative applications for generative AI.
Overall, the NVIDIA HGX H200 is a powerful new chip that is expected to accelerate the development of generative AI. It is a valuable tool for researchers, startups, and large enterprises that are working on the cutting edge of AI.