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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 Thamsen, Lauritz and Kulagina, Svetlana and Will, Jonathan and Meyerhenke, Henning and Kao, Odej (2021). Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters. 2021 IEEE International Conference on Big Data. IEEE, to appear.


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.


Behnke, Ilja and Thamsen, Lauritz and Kao, Odej (2019). Héctor: A Framework for Testing IoT Applications Across Heterogeneous Edge and Cloud Testbeds. 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion. ACM, 15–20.


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Contact

Lauritz Thamsen
+49 30 314-24539
TEL
1210