ARTICLE AD BOX
NVIDIA has introduced the H200 NVL PCIe GPU, a new addition to its Hopper architecture, aimed at improving AI and high-performance computing (HPC) applications for enterprise servers. Unveiled at the Supercomputing 2024 conference, the H200 NVL offers a lower-power, air-cooled design that is ideal for data centers with flexible configurations, according to NVIDIA.
Benefits of the H200 NVL GPU
The H200 NVL GPU is designed to accommodate the needs of data centers with enterprise racks that are 20kW and below, which predominantly use air cooling. This makes it a crucial component for providing granularity in node deployment, allowing organizations to optimize their computing power efficiently. The GPU offers a 1.5x increase in memory and a 1.2x increase in bandwidth over its predecessor, the NVIDIA H100 NVL, enabling faster AI model fine-tuning and inference performance.
Technological Enhancements
Complementing the hardware capabilities of H200 NVL is NVIDIA's NVLink technology, which offers GPU-to-GPU communication speeds seven times faster than the fifth-generation PCIe. This advancement is particularly beneficial for high-demand tasks such as large language model inference and fine-tuning.
Industry Adoption and Use Cases
Enterprises across various sectors are already leveraging the H200 NVL for diverse applications. Dropbox uses NVIDIA’s accelerated computing to enhance its AI and machine learning capabilities, while the University of New Mexico applies it in research areas such as genomics and climate modeling. These use cases underscore the GPU's potential to drive efficiency and innovation in AI and HPC workloads.
Availability and Ecosystem Support
Major technology companies, including Dell Technologies, Hewlett Packard Enterprise, Lenovo, and Supermicro, are expected to support the H200 NVL in a variety of configurations. NVIDIA's global systems partners will begin offering platforms featuring the H200 NVL in December. Additionally, NVIDIA is developing an Enterprise Reference Architecture to assist partners and customers in deploying high-performance AI infrastructure at scale.
For further details, visit the official NVIDIA blog here.
Image source: Shutterstock