Nvidia moves Hopper GPUs for AI into full production

by | Sep 20, 2022 | Technology

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

Nvidia announced today that the Nvidia H100 Tensor Core graphics processing unit (GPU) is in full production, with global tech partners planning in October to roll out the first wave of products and services based on the Nvidia Hopper architecture.

Nvidia CEO Jensen Huang made the announcement at Nvidia’s online GTC fall event.

Unveiled in April, H100 is built with 80 billion transistors and has a range of technology breakthroughs. Among them are the powerful new Transformer Engine and an Nvidia NVLink interconnect to accelerate the largest artificial intelligence (AI) models, like advanced recommender systems and large language models, and to drive innovations in such fields as conversational AI and drug discovery.

“Hopper is the new engine of AI factories, processing and refining mountains of data to train models with trillions of parameters that are used to drive advances in language-based AI, robotics, healthcare and life sciences,” said Jensen Huang, founder and CEO of Nvidia, in a statement. “Hopper’s Transformer Engine boosts performance up to an order of magnitude, putting large-scale AI and HPC within reach of companies and researchers.”

Event
MetaBeat 2022
MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.

Register Here

In addition to Hopper’s architecture and Transformer Engine, several other key innovations power the H100 GPU to deliver the next massive leap in Nvidia’s accelerated compute data center platform, including second-generation Multi-Instance GPU, confidential computing, fourth-generation Nvidia NVLink and DPX Instructions.

“We’re super excited to announce that the Nvidia H100 is now in full production,” said Ian Buck, general m …

Article Attribution | Read More at Article Source

Share This