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Adaptive Resource Management (ARM)

Lupe

One of the areas we work on in the DOS group is adaptive resource management for data-intensive distributed applications, aiming at systems that automatically adapt to workloads and environments. Learn more...

Team

Lupe

Research

Aiming to make it easier to run data-intensive applications efficiently on distributed computing infrastructures from small devices to large-scale clusters, we work on adaptive resource management, following an iterative systems research approach.

Current research directions include:

Recent Publications

Bader, Jonathan and Lehmann, Fabian and Groth, Alexander and Thamsen, Lauritz and Scheinert, Dominik and Will, Jonathan and Leser, Ulf and Kao, Odej (2022). Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures. 41th International Performance Computing and Communications Conference 2022. IEEE, to appear.


Will, Jonathan and Thamsen, Lauritz and Bader, Jonathan and Scheinert, Dominik and Kao, Odej (2022). Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing. IEEE International Conference on Cloud Engineering (IC2E). IEEE, to appear.


Zhu, Houkun and Scheinert, Dominik and Thamsen, Lauritz and Gontarska, Kordian and Kao, Odej (2022). Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning. IEEE International Conference on Cloud Engineering (IC2E). IEEE, to appear.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210