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PAID-Improve IO scalability of CitcomS 

Lijun Liu, University of Illinois at Urbana-Champaign

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Darren Adams, Ryan Mokos, Lijun Liu, Jiashun Hu, Quan Zhou, Edward Karrels, Lin Chen
Is I/O limiting your ability to do your science? Recent examination of I/O performance at several supercomputing centers showed that many applications were I/O limited; some were unaware that they could do much better. This project will be extending some existing tools to help identify sources of I/O performance problems and providing new tools to help improve I/O performance with minimum impact on applications. This project is looking for teams interested in (a) evaluating I/O performance and choice of I/O methods, (b)providing feedback on preferred I/O workflow (how you wish that it would work, not just how you've chosen to handle I/O in the pursuit of adequate performance), and (c) exploring the use of alternative I/O approaches including automatic performance tuning methods.