General Information
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Dr. Eisenhauer’s research focuses systems and middleware, particularly in the context of high performance computing and communication. His recent work focus on streaming data, customizable communication protocols and efficient metadata handling.
Dr. Eisenhauer’s teaching is focused on distributed and high performance computing systems. His research is student-focused and actively involves both graduate and undergraduate students.
Unlocking the Unusable: A Proactive Caching Framework for Reusing Partial Overlapped Data, C Guo, N Podhorszki, G Eisenhauer, Z Xie, S Klasky, Z Cao, Proceedings of the 17th ACM Workshop on Hot Topics in Storage and File Systems, 2025. | |||||||||||||||
HPC I/O Innovations in the Exascale Era, G Eisenhauer, N Podhorszki, A Gainaru, S Klasky, J Gu, V Bolea, L Dulac, ..., The International Journal of High Performance Computing Applications, 2025. | |||||||||||||||
HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP, N Podhorszki, G Eisenhauer, T Kurc, Q Gong, Q Liu, J Chen, A Gainaru, Junmin Gu, Scott Klasky, Proceedings of the 2025 Supercomputing Asia Conference, 91-95. | |||||||||||||||
The Artificial Scientist--in-transit Machine Learning of Plasma Simulations, J Kelling, V Bolea, M Bussmann, A Checkervarty, A Debus, J Ebert, ..., arXiv preprint arXiv:2501.03383, 2025. | |||||||||||||||
To derive or not to derive: I/O libraries take charge of derived quantities computation, A Gainaru, N Podhorszki, L Dulac, Q Gong, S Klasky, G Eisenhauer, A Kougkas, XH Sun, J Lofstead, 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing.
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