Tag: exascale computing

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    ExaWind Simulation

    Large-scale computational fluid dynamics simulations face many challenges. Among them is the need to capture both large physical scales–like those of Earth’s atmospheric boundary layer–and small scales–like those of tiny eddies moving around a wind-turbine blade. Capturing all of these scales for a problem like four wind turbines in a wind farm requires using the full computing power of every processor in a large supercomputer. That’s the level of power behind the simulation visualized in this video. The results, however, are stunning. (Video and image credit: M. da Frahan et al.)

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    Exascale Simulations

    Capturing what goes on inside a combustion engine is incredibly difficult. It’s a problem that depends on turbulent flow, chemistry, heat transfer, and more. To represent all of those aspects in a numerical simulation requires enormous computational resources. It’s not simply the realm of a supercomputer; it requires some of the fastest supercomputers in existence.

    Exascale computing, like that used for the simulations in this video, is defined as at least 10^18 (floating-point) operations per second. For comparison, my PC has a recent, high-end graphics card, and it’s about a million times slower than that. These are absolutely gigantic simulations. (Image and video credit: N. Wimer et al.)