As a former research scientist at Google, Ian Goodfellow has had a direct hand in some of the more complex, promising frameworks set to power the future of deep learning in coming years. …
Whenever companies that sell compute components for a living get into the systems business, they usually have a good reason for doing so. …
The revolution in GPU computing started with games, and spread to the HPC centers of the world eight years ago with the first “Fermi” Tesla accelerators from Nvidia. …
It is hard to find a more hyperbolic keynote title than, “A New Computing Model” but given the recent explosion in capabilities in both hardware and algorithms that have pushed deep learning to the fore, Nvidia’s CEO keynote at this morning’s GPU Technology Conference kickoff appears to be right on target. …
With machine learning taking off among hyperscalers and others who have massive amounts of data to chew on to better serve their customers and traditional simulation and modeling applications scaling better across multiple GPUs, all server makers are in an arm’s race to see how many GPUs they can cram into their servers to make bigger chunks of compute available to applications. …
While GPUs are commonly used to accelerate massively parallel compute jobs that are behind simulations, media rendering, or machine learning algorithms, the next wave of growth could come from databases, thereby upsetting the balance of power in get another part of the datacenter infrastructure. …
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