Between the 256 GH200 “superchips” it’s made of, the system will pack an astonishing 144 TB of shared memory, which is 500 times more than Nvidia’s previous supercomputer, the DGX A100 ...

DGX A100 can deliver fine-grained allocation of computing power, using the Multi-Instance GPU capability in the NVIDIA A100 Tensor Core GPU. Administrators can assign resources that are right-sized ...

The DGX A100 is NVIDIA’s third generation AI supercomputer. It boasts 5 petaflops of computing power delivered by eight of the company’s new Ampere A100 Tensor Core GPUs.

“DGX Station A100 brings AI out of the data center with a server-class system that can plug in anywhere,” said Charlie Boyle, vice president and general manager of DGX systems at NVIDIA.

Introducing NVIDIA DGX A100 If playback doesn't begin shortly, try restarting your device. Videos you watch may be added to the TV's watch history and influence TV recommendations.

Today NVIDIA unveiled the NVIDIA DGX A100 AI system, delivering 5 petaflops of AI performance and consolidating the power and capabilities of an entire data center into a single flexible platform.

NVIDIA said a high-severity information-disclosure bug impacting its DGX A100 server line wouldn't be patched until early 2021.

Nvidia unveiled its Ampere graphics architecture and its most powerful computer yet: The DGX A100. Costing $199,000, this isn't a system made for gamers.

SANTA CLARA, Calif., May 14, 2020 (GLOBE NEWSWIRE) -- NVIDIA today unveiled NVIDIA DGX™ A100, the third generation of the world’s most advanced AI system, delivering 5 petaflops of AI ...

Nvidia unwrapped its Nvidia A100 artificial intelligence chip today, and CEO Jensen Huang called it the ultimate instrument for advancing AI.

The NVIDIA DGX A100 cluster consists of 24 nodes for 120 petaflops of compute power, making it the fastest "AI supercomputer" at the consortium's disposal.

NVIDIA DGX Station A100 The NVIDIA DGX Station A100 — the world’s only petascale workgroup server — accelerates demanding machine learning and data science workloads for teams working in ...