8 papers
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…
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…
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…
Nf-PEAK: Process-Based Energy Attribution for Nextflow Workflows on Kubernetes Clusters
Philipp Thamm, Somayeh Mohammadi, Kathleen West +3
Scientific workflows are pipelines of interdependent tasks. They are increasingly executed on shared Kubernetes clusters via workflow engines such as Nextflow. Their energy consump…
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…
Ichnos: A Carbon Footprint Estimator for Scientific Workflows
Kathleen West, Magnus Reid, Yehia Elkhatib +1
Scientific workflows facilitate the automation of data analysis, and are used to process increasing amounts of data. Therefore, they tend to be resource-intensive and long-running,…