As part of France’s national strategy to advance to the forefront of artificial intelligent research in Europe, the government will install a 14 petaflops supercomputer for the French National Center for Scientific Research (CNRS). …
If you are running applications in the HPC or AI realms, you might be in for some sticker shock when you shop for GPU accelerators – thanks in part to the growing demand of Nvidia’s Tesla cards in those markets but also because cryptocurrency miners who can’t afford to etch their own ASICs are creating a huge demand for the company’s top-end GPUs. …
It must be tough for the hyperscalers that are expanding into public cloud and the public cloud builders that also use their datacenters to run their own businesses to decide whether to hoard all of the new technologies that they can get their hands on for their own benefit, or to make money selling that capacity to others. …
Announcements of new iron are exciting, but it doesn’t get real until customers beyond the handful of elite early adopters can get their hands on the gear. …
At well over $150,000 per appliance, the Volta GPU based DGX appliances from Nvidia, which take aim at deep learning with framework integration and 8 Volta-accelerated nodes linked with NVlink, is set to appeal to the most bleeding edge of machine learning shops. …
One of the reasons why Nvidia has been able to quadruple revenues for its Tesla accelerators in recent quarters is that it doesn’t just sell raw accelerators as well as PCI-Express cards, but has become a system vendor in its own right through its DGX-1 server line. …
Graphics chip maker Nvidia has taken more than a year and carefully and methodically transformed its GPUs into the compute engines for modern HPC, machine learning, and database workloads. …
To a certain extent, Nvidia and AMD are not really selling GPU compute capacity as much as they are reselling just enough HBM memory capacity and bandwidth to barely balance out the HBM memory they can get their hands on, thereby justifying the ever-embiggening amount of compute their GPU complexes get overstuffed with. …
There are many reasons why Nvidia is the hardware juggernaut of the AI revolution, and one of them, without question, is the NVLink memory sharing port that started out on its “Pascal” P100 GOU accelerators way back in 2016. …
Here is a question for you. What is harder to get right now: 1,665 of Nvidia’s “Blackwell” B200 GPU compute engines or 10 megawatts of power for a four year contract in the Northeast region of the United States? …
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