• NVLink Takes GPU Acceleration To The Next Level

    May 4, 2016

    One of the breakthrough moments in computing, which was compelled by necessity, was the advent of symmetric multiprocessor, or SMP, clustering to make two or more processors look and act, as far as the operating system and applications were concerned, as a single, more capacious processor. With NVLink clustering for GPUs and for lashing GPUs to CPUs, Nvidia is bringing something as transformative as SMP was for CPUs to GPU accelerators.

    The NVLink interconnect has been in development for years, and is one of the “five miracles” that Nvidia CEO and co-founder Jen-Hsun Huang said at the GPU Technology Conference …

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  • Baidu Eyes Deep Learning Strategy in Wake of New GPU Options

    April 22, 2016

    This month Nvidia bolstered its GPU strategy to stretch further into deep learning, high performance computing, and other markets, and while there are new options to consider, particularly for the machine learning set, it is useful to understand what these new arrays of chips and capabilities mean for users at scale. As one of the companies directly in the lens for Nvidia with its recent wave of deep learning libraries and GPUs, Baidu has keen insight into what might tip the architectural scales—and what might still stay the same, at least for now.

    Back in December, when we talked to …

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  • Nvidia’s Tesla P100 Steals Machine Learning From The CPU

    April 21, 2016 Paul Teich

    Pattern analytics, deep learning, and machine learning have fueled a rapid rise in interest in GPU computing, in addition to GPU computing applications in high performance computing (HPC) and cloud-based data analytics.

    As a high profile example, Facebook recently contributed its “Big Sur” design to the Open Compute Project (OCP), for use specifically in training neural networks and implementing artificial intelligence (AI) at scale. Facebook’s announcement of Big Sur says “Big Sur was built with the Nvidia Tesla M40 in mind but is qualified to support a wide range of PCI-e cards,” pointing out how pervasive Nvidia’s Tesla …

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  • Drilling Down Into Nvidia’s “Pascal” GPU

    April 19, 2016

    Nvidia made a lot of big bets to bring its “Pascal” GP100 GPU to market and its first implementation of the GPU is aimed at its Tesla P100 accelerator for radically improving the performance of massively parallel workloads like scientific simulations and machine learning algorithms. The Pascal GPU is a beast, in all of the good senses of that word, and warrants a deep dive that was not possible on announcement day back at the GPU Technology Conference.

    We did an overview of the chip back on announcement day, as well as talking about Nvidia’s own DGX-1 hybrid server …

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  • Power9 Will Bring Competition To Datacenter Compute

    April 18, 2016

    The Power9 processor that IBM is working on in conjunction with hyperscale and HPC customers could be the most important chip that Big Blue has brought to market since the Power4 processor back in 2001. That was another world, back then, with the dot-com boom having gone bust and enterprises looking for a less expensive but beefy NUMA server on which to run big databases and transaction processing systems.

    The world that the Power9 processor will enter in 2017 is radically changed. A two-socket system has more compute, memory, and I/O capacity and bandwidth than those behemoths from a decade …

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  • Nvidia Lead Details Future Convergence of Supercomputing, Deep Learning

    April 15, 2016

    Deep learning could not have developed at the rapid pace it has over the last few years without companion work that has happened on the hardware side in high performance computing. While the applications and requirements for supercomputers versus neural network training are quite different (scalability, programming, etc.) without the rich base of GPU computing, high performance interconnect development, memory, storage, and other benefits from the HPC set, the boom around deep learning would be far quieter.

    In the midst of this convergence, Marc Hamilton has watched advancements on the HPC side over the years, beginning in the mid-1990s …

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  • Nvidia Not Sunsetting Tesla Kepler And Maxwell GPUs Just Yet

    April 7, 2016

    Switch chips have a very long technical and economic lives, considerably longer than that of a Xeon processor used in a server – something on the order of seven or eight years compared to three or four. As it turns out, the various GPUs used in Nvidia’s Tesla accelerators look like they, too, will have very long technical and economic lives.

    Even after a new technology is introduced, sometimes the old one can be had at a much cheaper price and therefore continues to be a good price/performer even after it has been presumably obsoleted by an improved product. Its …

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  • IBM Unfolds Power Chip Roadmap Out Past 2020

    April 7, 2016

    There are two things that underdogs have to do to take a big bite out of a market. First, they have to tell prospective customers precisely what the plan is to develop future products, and then they have to deliver on that roadmap. The OpenPower collective behind the Power chip developed did the first thing at its eponymous summit in San Jose this week, and now it is up to the OpenPower partners to do the hard work of finishing the second.

    Getting a chip as complex as a server processor into the field, along with its chipsets and memory …

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  • IBM Watson CTO on What’s Ahead for Cognitive Computing

    April 7, 2016

    After close to twenty years at IBM, where he began as an IBM Fellow and Chief Architect for the SOA Foundation, Rob High has developed a number of core technologies that back Big Blue’s enterprise systems, including the suite of tools behind IBM WebSphere, and more recently, those that support the wide-ranging ambitions of the Watson cognitive computing platform.

    Although High gave the second day keynote this afternoon at the GPU Technology Conference, there was no mention of accelerated computing. Interestingly, while the talk was about software, specifically the machine learning behind Watson, there was also very little about the …

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  • Inside The Future Google Rackspace Power9 System

    April 6, 2016

    The OpenPower effort to create an alternative to the Xeon architecture in the datacenter just got a whole lot more real now that hyperscaler Google and cloud builder Rackspace Hosting have agreed to partner on a future server design based on IBM’s future Power9 processor that both companies intend to deploy in their datacenters.

    Google, as one of the five founding members of the OpenPower Foundation in the summer of 2013, is always secretive about its server, storage, and switching platforms, absent the occasional glimpse that only whets the appetite for more disclosures. But at last year’s OpenPower Summit, Gordon …

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