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20212026
most citedSizey: Memory-Efficient Execution of Scientific Workflow Tasks

9 citations · 22 across the 12 of their papers we have counts for

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Showing 2025 · cs.DCShow all

6 papers · 2 filters

cs.DC2025

What happens when nanochat meets DiLoCo?

Alexander Acker, Soeren Becker, Sasho Nedelkoski +3

Although LLM training is typically centralized with high-bandwidth interconnects and large compute budgets, emerging methods target communication-constrained training in distribute…

cs.DC2025

Learning Process Energy Profiles from Node-Level Power Data

Jonathan Bader, Julius Irion, Jannis Kappel +4

The growing demand for data center capacity, driven by the growth of high-performance computing, cloud computing, and especially artificial intelligence, has led to a sharp increas…

cs.DC2025

Optimizing Microgrid Composition for Sustainable Data Centers

Julius Irion, Philipp Wiesner, Jonathan Bader +1

As computing energy demand continues to grow and electrical grid infrastructure struggles to keep pace, an increasing number of data centers are being planned with colocated microg…

cs.DC2025

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art

Jonathan Bader, Kathleen West, Soeren Becker +5

Scientific workflow management systems support large-scale data analysis on cluster infrastructures. For this, they interact with resource managers which schedule workflow tasks on…

cs.DC2025

Flora: Efficient Cloud Resource Selection for Big Data Processing via Job Classification

Jonathan Will, Lauritz Thamsen, Jonathan Bader +1

Distributed dataflow systems like Spark and Flink enable data-parallel processing of large datasets on clusters of cloud resources. Yet, selecting appropriate computational resourc…

cs.DC2025

Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling

Jonathan Will, Nico Treide, Lauritz Thamsen +1

Distributed dataflow systems like Spark and Flink enable data-parallel processing of large datasets on clusters. Yet, selecting appropriate computational resources for dataflow job…