OpenAI won’t be getting Google’s latest, top-shelf TPUs, but that barely matters. Perhaps the bigger flex is that OpenAI ...

The V100 will first appear inside Nvidia's bespoke compute servers. Eight of them will come packed inside the $150,000 (~£150,000) DGX-1 rack-mounted server, which ships in the third quarter of 2017.

Today Inspur announced that their new NF5488M5 high-density AI server supports eight NVIDIA V100 Tensor Core GPUs in a 4U form factor. “The rapid development of AI keeps increasing the requirements ...

Nvidia has taken the wraps off its newest accelerator aimed at deep learning, the Tesla V100. Developed at a cost of $3 billion, the V100 packs 21 billion transistors laid down with TSMC's 12 ...

“We know that CPUs and GPUs are going to get denser and we have developed technologies that are available today which support a 500-watt chip the size of a V100 and we are working on the development ...

Built on a 12nm process, the V100 boasts 5,120 CUDA Cores, 16GB of HBM2 memory, an updated NVLink 2.0 interface and is capable of a staggering 15 teraflops of computational power.

At the heart of the Tesla V100 is NVIDIA's Volta GV100 GPU, which features a staggering 21.1 billion transistors on a die that measures 815mm 2 (this compares to 12 billion transistors and 610mm 2 ...

NVIDIA's super-fast Tesla V100 rocks 16GB of HBM2 that has memory bandwidth of a truly next level 900GB/sec, up from the 547GB/sec available on the TITAN Xp, which costs $1200 in comparison.

The T4, which essentially uses the same processor architecture as Nvidia’s RTX cards for consumers, slots in-between the existing Nvidia V100 and P4 GPUs on the Google Cloud Platform.

NVIDIA's new Tesla V100 is a massive GPU with the Volta GPU coming in at a huge 815mm square, compared to the Pascal-based Tesla P100 at 600mm square.

Nvidia's V100 GPUs have more than 120 teraflops of deep learning performance per GPU. That throughput effectively takes the speed limit off AI workloads. In a blog post, ...