• Big Bang For The Buck Jump With Volta DGX-1

    May 19, 2017

    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. The company has also engineered new adapter cards specifically aimed at hyperscalers who want to crank up the performance on their machine learning inference workloads with a cheaper and cooler Volts GPU.

    Nvidia does not break out revenues for the DGX-1 line separately from other Tesla and GRID accelerator product sales, but we …

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  • Risk or Reward: First Nvidia DGX-1 Boxes Hit the Cloud

    April 11, 2017

    If you can’t beat the largest cloud players at economies of scale, the only option is to try to outrun them in performance, capabilities, or price.

    While go head to head with Amazon, Google, Microsoft, or IBM on cloud infrastructure prices is a challenge, one way to gain an edge is by being the first to deliver bleeding-edge hardware to those users with emerging, high-value workloads. The trick is to be at the front of the wave, often with some of the most expensive iron, which is risky with AWS and others nipping at heels and quick to follow. It …

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  • Japan to Unveil Pascal GPU-Based AI Supercomputer

    March 6, 2017

    A shared appetite for high performance computing hardware and frameworks is pushing both supercomputing and deep learning into the same territory. This has been happening in earnest over the last year, and while most efforts have been confined to software and applications research, some supercomputer centers are spinning out new machines dedicated exclusively to deep learning.

    When it comes to such supercomputing sites on the bleeding edge, Japan’s RIKEN Advanced Institute for Computational Science is at the top of the list. The center’s Fujitsu-built K Computer is the seventh fastest machine on the planet according to the Top 500 rankings …

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  • Nvidia CEO’s “Hyper-Moore’s Law” Vision for Future Supercomputers

    November 28, 2016

    Over the last year in particular, we have documented the merger between high performance computing and deep learning and its various shared hardware and software ties. This next year promises far more on both horizons and while GPU maker Nvidia might not have seen it coming to this extent when it was outfitting its first GPUs on the former top “Titan” supercomputer, the company sensed a mesh on the horizon when the first hyperscale deep learning shops were deploying CUDA and GPUs to train neural networks.

    All of this portends an exciting year ahead and for once, the mighty CPU …

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  • How Nvidia’s Own Saturn V DGX-1 Cluster Stacks Up

    November 14, 2016

    Not all of the new and interesting high performance computing systems are always in the upper echelons of the Top 500 supercomputing list, which was announced at the opening of the SC16 supercomputing conference in Salt Lake City this week. Sometimes, an intriguing system breaks into the list outside of the top ten or twenty most powerful machines in the bi-annual rankings of number-crunching performance, and such is the case with the new “Saturn V” supercomputer built by Nvidia using its latest GPUs and interconnects.

    The Saturn V system, nick-named of course for the NASA launch vehicle that eventually …

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  • DGX-1 Is Nvidia’s Deep Learning System For Newbies

    April 6, 2016

    Whenever companies that sell compute components for a living get into the systems business, they usually have a good reason for doing so. There is a delicate balance between addressing a market need quickly and competing with your own channel partners Intel, AMD, and several ARM server chip makers have walked, and Nvidia is toeing that line with its new DGX-1 system for deep learning.

    The DGX-1 is not just a server, but a system, and this is a key differentiation that might not be obvious from the way it was presented during the opening keynote at the GPU Technology …

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