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GPU-Based Parallel Computing: A New Computational Approach and its Applications to Nuclear Engineering

Kai Huang, Volodymyr Kindratenko, Rizwan-uddin
Department of Nuclear, Plasma, & Radiological Engineering, University of Illinois at Urbana-Champaign, 104 South Wright Street, Urbana, IL 61801, USA
Proc. of ANS Annual Meeting 2009, (2009)

@article{huang2009gpu,

   title={GPU-Based Parallel Computing: A New Computational Approach and its Applications to Nuclear Engineering},

   author={Huang, Kai and Kindratenko, Volodymyr and Rizwan-uddin},

   booktitle={ANS Annual Meeting},

   year={2009}

}

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Faster speed and higher accuracy are, and will always be pursued by computational scientists and engineers. To achieve these goals, single-core microprocessors were assembled to arrive at "parallel computing". This parallelism is recently extended to chiplevel with the emergence of multi- and many-core architectures-that is, roughly, adding more cores onto a single chip-in both Central Processing Units (CPUs) and Graphics Processing Units (GPUs). As a result, scientific computing is rapidly moving toward many-core parallelism. Modeling and simulation in nuclear science and engineering relies heavily on computational power. Nuclear engineers took advantage of parallelization to advance the simulations of neutronics, thermal hydraulics, materials, plasma physics, etc [2, 3]. The field is expected to benefit significantly from the new many-core GPU technology.
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