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TU Berlin

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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

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.


Will, Jonathan and Bader, Jonathan and Thamsen, Lauritz (2020). Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs. 2020 IEEE International Conference on Big Data. IEEE, 2851–2856.


Will, Jonathan and Thamsen, Lauritz and Scheinert, Dominik and Bader, Jonathan and Kao, Odej (2021). C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds. International Conference on Cloud Engineering. IEEE, 43-52.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210