Improving I/O Performance for Exascale Applications Through Online Data Layout Reorganization

@article{Wan2022ImprovingIP,
  title={Improving I/O Performance for Exascale Applications Through Online Data Layout Reorganization},
  author={Lipeng Wan and Axel Huebl and Junmin Gu and Franz Poeschel and Ana Gainaru and Ruonan Wang and Jieyang Chen and Xin Liang and Dmitry Ganyushin and Todd Munson and Ian T. Foster and Jean-Luc Vay and Norbert Podhorszki and Kesheng Wu and Scott Klasky},
  journal={IEEE Transactions on Parallel and Distributed Systems},
  year={2022},
  volume={33},
  pages={878-890}
}
The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O… 
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