Nvidia credited record sales of its Tesla V100 training GPUs and T4 inference GPUs for moving its data center business from recovery mode to double-digit growth. The Santa Clara, Calif.- ...

compared GH200 clusters with AMD’s MI250X and Nvidia’s A100 and V100 chips in supercomputers like Frontier, Leonardo, and Summit. The GH200 showed impressive results for climate simulations ...

First we'll take detailed look at the Tesla V100, one of the NVIDIA models that has been favored for HPC applications. In a subsequent topic, we do a similar deep dive into the Quadro RTX 5000, a GPU ...

However, we are getting close to the GPU memory wall. It requires 800 NVIDIA V100 GPUs just to fit a trillion parameter model for training, and such clusters are simply out of reach for most data ...

Taiwania 2 was built using Nvidia's V100 GPUs and has played a crucial role in advancing AI capabilities within Taiwan. However, as AI continues to evolve rapidly, there is an increasing need for more ...

Nvidia said this will make the AI Research SuperCluster ... models compared to an earlier cluster with 22,000 Nvidia V100 GPUs. These DGX A100 systems are connected over an Nvidia Quantum 200 ...

The Visualization partition is composed of three NVIDIA Tesla V100 GPUs, 48 CPU cores, and 1.1TiB of memory. Pronghorn signals the University’s commitment to continue to enhance the research ...