5 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…
Strategies to Measure Energy Consumption Using RAPL During Workflow Execution on Commodity Clusters
Philipp Thamm, Ulf Leser
In science, problems in many fields can be solved by processing datasets using a series of computationally expensive algorithms, sometimes referred to as workflows. Traditionally,…