In April 2025, the U.S. expanded restrictions to include the Nvidia H20 chip, a China-specific version designed to comply ...

TensorWave has built North America's largest AMD AI cluster with 8,192 liquid-cooled MI325X GPUs, delivering 21 exaFLOPS of FP8 throughput. It’s a bold move against NVIDIA’s dominance and marks ROCm’s ...

China reportedly plans to build vast data centers powered by over 115,000 high-end (and restricted by US bans) NVIDIA AI GPUs ...

China plans to build at least 39 data centers in the desert regions of Xinjiang and Qinghai, outfitted with over 115,000 ...

China plans to build 39 AI data centers using over 115,000 restricted Nvidia GPUs, with 70% going to a massive site in ...

The global research landscape is undergoing a seismic shift. Universities worldwide are deploying NVIDIA’s H200 Tensor Core ...

CRSi announces a USD 54 million order for AI servers in the United Kingdom 2CRSi SA 2CRSi SA: 2CRSi announces a USD 54 million order for AI servers in the United Kingdom 08-Jul-2025 ...

CUDA and Tensor Cores are some of the most prominent specs on an NVIDIA GPU. These cores are the fundamental computational blocks that allow a GPU to perform a bunch of tasks such as video ...

NVIDIA GPUs, particularly the H100 and H200, outperform Google’s TPU V6E in terms of VRAM capacity, throughput, and scalability, making them better suited for large-scale AI workloads.

By harnessing the CUDA-Q platform and 1,024 Nvidia H100 Tensor Core GPUs on the Eos supercomputer, Google achieved one of the most extensive dynamical simulations of quantum devices to date.

The H100 Tensor Core GPUs were added to a family of Nvidia GPUs and software that IBM already supported. At the time, IBM said the Nvidia H100 Tensor Core GPU could enable up to 30X faster ...

The company said the rack-scale machine can conduct large language model inferencing 30 times faster than the predecessor H100 Tensor Core GPU and is 25 times more energy-efficient.