109 citations · 463 across the 69 of their papers we have counts for
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The Common Workflow Scheduler Interface: Status Quo and Future Plans
Fabian Lehmann, Jonathan Bader, Lauritz Thamsen +1
Nowadays, many scientific workflows from different domains, such as Remote Sensing, Astronomy, and Bioinformatics, are executed on large computing infrastructures managed by resour…
Towards a Peer-to-Peer Data Distribution Layer for Efficient and Collaborative Resource Optimization of Distributed Dataflow Applications
Dominik Scheinert, Soeren Becker, Jonathan Will +2
Performance modeling can help to improve the resource efficiency of clusters and distributed dataflow applications, yet the available modeling data is often limited. Collaborative…
Predicting Dynamic Memory Requirements for Scientific Workflow Tasks
Jonathan Bader, Nils Diedrich, Lauritz Thamsen +1
With the increasing amount of data available to scientists in disciplines as diverse as bioinformatics, physics, and remote sensing, scientific workflow systems are becoming increa…
Lotaru: Locally Predicting Workflow Task Runtimes for Resource Management on Heterogeneous Infrastructures
Jonathan Bader, Fabian Lehmann, Lauritz Thamsen +2
Many resource management techniques for task scheduling, energy and carbon efficiency, and cost optimization in workflows rely on a-priori task runtime knowledge. Building runtime…
Karasu: A Collaborative Approach to Efficient Cluster Configuration for Big Data Analytics
Dominik Scheinert, Philipp Wiesner, Thorsten Wittkopp +3
Selecting the right resources for big data analytics jobs is hard because of the wide variety of configuration options like machine type and cluster size. As poor choices can have…
Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
Jonathan Will, Lauritz Thamsen, Dominik Scheinert +1
Distributed dataflow systems such as Apache Spark or Apache Flink enable parallel, in-memory data processing on large clusters of commodity hardware. Consequently, the appropriate…
Towards a Real-Time IoT: Approaches for Incoming Packet Processing in Cyber-Physical Systems
Ilja Behnke, Christoph Blumschein, Robert Danicki +3
Embedded real-time devices for monitoring, controlling, and collaboration purposes in cyber-physical systems are now commonly equipped with IP networking capabilities. However, the…
FedZero: Leveraging Renewable Excess Energy in Federated Learning
Philipp Wiesner, Ramin Khalili, Dennis Grinwald +3
Federated Learning (FL) is an emerging machine learning technique that enables distributed model training across data silos or edge devices without data sharing. Yet, FL inevitably…
Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services
Demetris Trihinas, Lauritz Thamsen, Jossekin Beilharz +1
Energy consumption and carbon emissions are expected to be crucial factors for Internet of Things (IoT) applications. Both the scale and the geo-distribution keep increasing, while…
How Workflow Engines Should Talk to Resource Managers: A Proposal for a Common Workflow Scheduling Interface
Fabian Lehmann, Jonathan Bader, Friedrich Tschirpke +2
Scientific workflow management systems (SWMSs) and resource managers together ensure that tasks are scheduled on provisioned resources so that all dependencies are obeyed, and some…