31 citations · 407 across the 77 of their papers we have counts for
8 papers · 2 filters
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…
Carbon-Awareness in CI/CD
Henrik Claßen, Jonas Thierfeldt, Julian Tochman-Szewc +2
While the environmental impact of digitalization is becoming more and more evident, the climate crisis has become a major issue for society. For instance, data centers alone accoun…
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…
Towards Benchmarking Power-Performance Characteristics of Federated Learning Clients
Pratik Agrawal, Philipp Wiesner, Odej Kao
Federated Learning (FL) is a decentralized machine learning approach where local models are trained on distributed clients, allowing privacy-preserving collaboration by sharing mod…
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…
Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems
Dominik Scheinert, Fabian Casares, Morgan K. Geldenhuys +2
Stream processing has become a critical component in the architecture of modern applications. With the exponential growth of data generation from sources such as the Internet of Th…
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…
Vessim: A Testbed for Carbon-Aware Applications and Systems
Philipp Wiesner, Ilja Behnke, Paul Kilian +2
To reduce the carbon footprint of computing and stabilize electricity grids, there is an increasing focus on approaches that align the power usage of IT infrastructure with the ava…