activity
20242026
collaborators

7 papers

cs.DC2026

How Accurately Can the Energy Use of Spark Applications Be Estimated Based on Resource Utilisation?

Youssef Moawad, Kathleen West, Vasilis Bountris +3

Distributed batch data processing applications are widely executed on cloud-based resources where restricted user access to node-level hardware energy counters hinders transparent…

cs.DC2026

Ichnos+: Estimating the Carbon Footprint of Scientific Workflows Using Fitted Power Models

Kathleen West, Youssef Moawad, Philipp Thamm +5

As data-intensive scientific workflows scale to facilitate the automation of analysis of increasing amounts of data, their resource-intensive and long-running execution incurs sign…

cs.DC2026

Augur: Pre-Execution Energy Prediction for Workflow Tasks in Heterogeneous Clusters

Kathleen West, Vasilis Bountris, Philipp Thamm +3

Scientific workflows are widely used to process large quantities of data, leading to significant energy consumption and carbon emissions. To reduce this environmental impact, energ…

cs.DC2026

A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows

Kathleen West, Youssef Moawad, Fabian Lehmann +4

Scientific workflows are critical to scientific data analysis and often involve computationally intensive processing of large datasets on compute clusters. As such, their execution…

cs.DC2025

HyProv: Hybrid Provenance Management for Scientific Workflows

Vasilis Bountris, Lauritz Thamsen, Ulf Leser

Provenance plays a crucial role in scientific workflow execution, for instance by providing data for failure analysis, real-time monitoring, or statistics on resource utilization f…

cs.DC2025

Exploring the Potential of Carbon-Aware Execution for Scientific Workflows

Kathleen West, Fabian Lehmann, Vasilis Bountris +3

Scientific workflows are widely used to automate scientific data analysis and often involve processing large quantities of data on compute clusters. As such, their execution tends…