• The Biggest Shift in Supercomputing Since GPU Acceleration

    June 22, 2017

    For years, the pace of change in large-scale supercomputing neatly tracked with the curve of Moore’s Law. As that swell flattens, and as the competitive pressure ticks up to build productive exascale supercomputers in the next few years, HPC has been scrambling to find the silver bullet architecture to reach sustained exascale performance. And as it turns out, there isn’t one.

    But there is something else—something few saw coming three years ago, has less to do with hardware than it does a shift in how we approach massive-scale simulations, and is happening so fast that too-far-ahead-of-time procurements are …

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  • Unifying Massive Data at Cloud Scale

    June 9, 2017

    Enterprises continue to struggle with the issue of data: how to process and move the massive amounts that are coming in from multiple sources, how to analyze the different types of data to best leverage its capabilities, and how to store and unify it across various environments, including on-premises infrastructure and cloud environments. A broad array of major storage players, such as Dell EMC, NetApp and IBM are building out their offerings to create platforms that can do a lot of those things.

    MapR Technologies, which made its bones with its commercial Hadoop distribution, is moving in a similar direction. …

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  • Machine Learning on Stampede2 Supercomputer to Bolster Brain Research

    May 31, 2017 Donna Loveland

    In our ongoing quest to understand the human mind and banish abnormalities that interfere with life we’ve always drawn upon the most advanced science available. During the last century, neuroimaging – most recently, the Magnetic Resonance Imaging scan (MRI) – has held the promise of showing the connection between brain structure and brain function.

    Just last year, cognitive neuroscientist David Schnyer and colleagues Peter Clasen, Christopher Gonzalez, and Christopher Beevers published a compelling new proof of concept in Psychiatry Research: Neuroimaging. It suggests that machine learning algorithms running on high-performance computers to classify neuroimaging data may deliver the most …

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  • Logistics in Application Path of Neural Networks

    May 25, 2017

    Accurately forecasting resource demand within the supply chain has never been easy, particular given the constantly changing nature of the data over periods of time.

    What may have been true in measurements around demand or logistics one minute might be entirely different an hour, day or week later, which can throw off a short-term load forecast (STLF) and lead to costly over- or under-estimations, which in turn can lead to too much or too little supply.

    To improve such forecasts, there are multiple efforts underway to create new models that can more accurately predict load needs, and while they have …

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  • FPGA Startup Gathers Funding Force for Merged Hyperscale Inference

    May 22, 2017

    Around this time last year, we delved into a new FPGA-based architecture that targeted efficient, scalable machine learning inference from startup DeePhi Tech. The company just rounded out its first funding effort with an undisclosed sum with major investors, including Banyan Capital and as we learned this week, FPGA maker Xilinx.

    As that initial article details, the Stanford and Tsinghua University-fed research focused on network pruning and compression at low precision with a device that could be structured for low latency and custom memory allocations. These efforts were originally built on Xilinx FPGA hardware and given this first round of …

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  • 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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  • Cray Supercomputing as a Service Becomes a Reality

    May 16, 2017

    For a mature company that kickstarted supercomputing as we know it, Cray has done a rather impressive job of reinventing itself over the years.

    From its original vector machines, to HPC clusters with proprietary interconnects and custom software stacks, to graph analytics appliances engineered in-house, and now to machine learning, the company tends not to let trends in computing slip by without a new machine.

    However, all of this engineering and tuning comes at a cost—something that, arguably, has kept Cray at bay when it comes to reaching the new markets that sprung up in the “big data” days of …

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  • When Will AI Replace Traditional Supercomputing Simulations?

    May 15, 2017

    The science fiction of a generation ago predicted a future in which humans were replaced by the reasoning might of a supercomputer. But in an unexpected twist of events, it appears the it is the supercomputer’s main output—scientific simulations—that could be replaced by an even higher order of intelligence.

    While we will always need supercomputing hardware, the vast field of scientific computing, or high performance computing, could also be in the crosshairs for disruptive change, altering the future prospects for scientific code developers, but opening new doors in more energy-efficient, finer-grained scientific discovery. With code that can write itself based …

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  • HPC to Deep Learning from an Asian Perspective

    May 15, 2017 Laurence Liew

    Big data, data science, machine learning, and now deep learning are all the rage and have tons of hype, for better—and in some ways, for worse. Advancements in AI such as language understanding, self-driving cars, automated claims, legal text processing, and even automated medical diagnostics are already here or will be here soon.

    In Asia, several countries have made significant advancements and investments into AI, leveraging their historical work in HPC.

    China now owns the top three positions in the Top500 with Sunway TaihuLight, Tianhe-2, and Tianhe, and while Tianhe-2 and Tianhe were designed for HPC style workloads, TaihuLight is …

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  • Nvidia’s Tesla Volta GPU Is The Beast Of The Datacenter

    May 10, 2017

    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 do so has meant staying on the cutting edge of many technologies, and with the much-anticipated but not very long-awaited “Volta” GP100 GPUs, the company is once again skating on the bleeding edge of several different technologies.

    This aggressive strategy allows Nvidia to push the performance envelope on GPUs and therefore maintain its lead over CPUs for the parallel workloads it is targeting while at the same time setting up …

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