• DOE to Fund $42M for HPC Cooling Systems

    WASHINGTON, D.C. — The U.S. Department of Energy today announced up to $42 million in funding for “high-performance energy efficient cooling solutions for data centers.” More about the COOLERCHIPS funding opportunity, and details on how to apply can be found at: ARPA-E eXCHANGE. Noting that cooling accounts for up to 40 percent of data center energy usage, DOE’s Advanced Research Projects Agency-Energy (ARPA-E) will fund projects seeking to reduce power consumption and lower the data center’s operational carbon footprint. Data centers consume 2 percent of total electrical use today, but that number is growing. The overall IT business – with [READ MORE…]

Featured Stories

Featured Resource

The Cray CS300 Cluster ‘s Warm Water Cooling Is at the Forefront of an HPC Industry Trend

This Technology Spotlight reviews the liquid cooling trend and the innovative use of warm water cooling in the Cray CS300 cluster supercomputer to reduce capital expense and operating costs. Download this white paper to learn more.

HPC Newsline

Industry Perspectives

  • …today’s situation is clear: HPC is struggling with reliability at scale. Well over 10 years ago, Google proved that commodity hardware was both cheaper and more effective for hyperscale processing when controlled by software-defined systems, yet the HPC market persists with its old-school, hardware-based paradigm. Perhaps this is due to prevailing industry momentum or working within the collective comfort zone of established practices. Either way, hardware-centric approaches to storage resiliency need to go.

  • New, Open DPC++ Extensions Complement SYCL and C++

    In this guest article, our friends at Intel discuss how accelerated computing has diversified over the past several years given advances in CPU, GPU, FPGA, and AI technologies. This innovation drives the need for an open and cross-platform language that allows developers to realize the potential of new hardware, minimizes development cost and complexity, and maximizes reuse of their software investments.

RSS Featured from insideBIGDATA

  • Enabling Federated Querying & Analytics While Accelerating Machine Learning Projects
    In this special guest feature, Brendan Newlon, Solutions Architect at Stardog, indicates that for an increasing number of organizations, a semantic data layer powered by an enterprise knowledge graph provides the solution that enables them to connect relevant data elements in their true context and provide greater meaning to their data.

Editor’s Choice

  • Frontier Named No. 1 Supercomputer on TOP500 List and ‘First True Exascale Machine’

    Hamburg — This morning, AMD’s long comeback from trampled HPC also-ran – a comeback that began in 2017 when company executives told skeptical press and industry analysts to expect price/performance chip superiority over Intel – reached a high point (not to say an end point) with the news that the U.S. Department of Energy’s Frontier supercomputer, an HPE-Cray EX system powered by AMD CPUs and GPUs, has not only been named the world’s most powerful supercomputer, it also is the first system to exceed the exascale (1018 calculations/second) milestone. This may not come as a  surprise to many in the [READ MORE…]

  • Chip Geopolitics: If China Invades, Make Taiwan ‘Unwantable’ by Destroying TSMC, Military Paper Suggests

    US military planners are taking notice of a suggestion by two military scholars calling for the destruction of semiconductor foundry company Taiwan Semiconductor Manufacturing Co. (TSMC), whose fabs produce advanced microprocessors used in HPC and AI, in the event China invades the island nation A news story in today’ edition of Data Center Times cites the Nikkei Asia news service and a paper in the U.S. Army War College’s scholarly journal, Parameters, discussing the possibility of Taiwan adopting “’a scorched earth policy’ and wipe out its own semiconductor foundries in the wake of any Chinese invasion as a deterrent, U.S. [READ MORE…]

  • How Machine Learning Is Revolutionizing HPC Simulations

    Physics-based simulations, that staple of traditional HPC, may be evolving toward an emerging, AI-based technique that could radically accelerate simulation runs while cutting costs. Called “surrogate machine learning models,” the topic was a focal point in a keynote on Tuesday at the International Conference on Parallel Processing by Argonne National Lab’s Rick Stevens. Stevens, ANL’s associate laboratory director for computing, environment and life sciences, said early work in “surrogates,” as the technique is called, shows tens of thousands of times (and more) speed-ups and could “potentially replace simulations.” Surrogates can be looked at as an end-around to two big problems [READ MORE…]

  • Double-precision CPUs vs. Single-precision GPUs; HPL vs. HPL-AI HPC Benchmarks; Traditional vs. AI Supercomputers

    If you’ve wondered why GPUs are faster than CPUs, in part it’s because GPUs are asked to do less – or, to be more precise, to be less precise. Next question: So if GPUs are faster than CPUs, why aren’t GPUs  the mainstream, baseline processor used in HPC server clusters? Again, in part it gets back to precision. In many workload types, particularly traditional HPC workloads, GPUs aren’t precise enough. Final question: So if GPUs and AI are inextricably linked, particularly for training machine learning models, and if GPUs are less precise than CPUs, does that mean AI is imprecise? [READ MORE…]

  • 6,000 GPUs: Perlmutter to Deliver 4 Exaflops, Top Spot in AI Supercomputing

    The U.S. National Energy Research Scientific Computing Center today unveiled the Perlmutter HPC system, a beast of a machine powered by 6,159 Nvidia A100 GPUs and delivering 4 exaflops of mixed precision performance. Perlmutter is based on the HPE Cray Shasta platform, including Slingshot interconnect, a heterogeneous system with both GPU-accelerated and CPU-only nodes. The system is being installed in two phases – today’s unveiling is Phase 1, which includes the system’s GPU-accelerated nodes and scratch file system. Phase 2 will add CPU-only nodes later in 2021. “That makes Perlmutter the fastest system on the planet on the 16- and 32-bit [READ MORE…]

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