NVIDIA launched the H200 NVL, a high-performance GPU for AI supercomputing.

Nvidia announced the availability of its newest data center-grade graphics processing unit, the H200 NVL, at the SC24 high-performance computing conference in Atlanta. The GPU is the latest addition to Nvidia's Hopper family of GPUs designed for data centers running on lower-power, air-cooled racks. According to the company, about 70% of enterprise data center floors run at 20,000-kilowatt hours and below, which allows for air cooling, making PCIe GPUs essential for flexibility since they don't require specialized cooling systems. The new GPU provides a 1.5-times memory efficiency increase and 1.2-times bandwidth increase over the H100 NVL, enabling businesses to fine-tune large language models within a few hours with up to 1.7-times faster performance when deployed.

The University of Mexico has tapped Nvidia's accelerated computing technology for scientific research and academic applications. Prof. Patrick Bridges, director of the UNM Center for Advanced Research Computing, stated: "As a public research university, our commitment to AI enables the university to be on the forefront of scientific and technological advancements. As we shift to H200 NVL, we'll be able to accelerate a variety of applications, including data science initiatives, bioinformatics and genomics research, physics and astronomy simulations, climate modeling and more."

To advance AI in scientific research, Nvidia released the open-source BioNeMo framework to assist with drug discovery and molecule design. "The convergence of AI, accelerated computing and expanding datasets offers unprecedented opportunities for the pharmaceutical industry, as evidenced by recent Nobel Prize wins in chemistry," said Kimberly Powell, vice president of healthcare at Nvidia. Additionally, Nvidia announced ALCHEMI, which allows researchers to optimize AI models via an NIM microservice. Using ALCHEMI, researchers can test chemical compounds and materials in a simulated virtual AI lab without building structures in an actual lab. According to Nvidia, the microservice can run on an H100 using a pretrained model for materials chemistry testing 100 times faster than without NIM. For example, evaluating 16 million structures could take months, but with the microservice it would take mere hours.

Nvidia announced two new NIM microservices for Earth-2, a platform for simulating and visualizing weather and climate conditions. According to a Bloomberg report, natural disasters were responsible for around $62 billion in insured losses during the first half of 2024, or about 70% more than the 10-year average. CorDiff NIM uses generative AI at kilometer-scale resolution for weather forecasting, trained on the Weather Research and Forecasting model to generate patterns at 12 times higher resolution. CorDiff NIM runs 500 times faster and is 100,000 times more energy efficient than traditional prediction using central processing units. FourCastNet provides global, medium-range, lower-resolution forecasts and can provide a forecast 5,000 times faster than traditional numerical weather models.