activity
20222025
most citedLotaru: Locally Estimating Runtimes of Scientific Workflow Tasks in Heterogeneous Clusters

20 citations · 99 across the 15 of their papers we have counts for

collaborators

17 papers

cs.DC2025

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

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★ 5 cited

WOW: Workflow-Aware Data Movement and Task Scheduling for Dynamic Scientific Workflows

Fabian Lehmann, Jonathan Bader, Friedrich Tschirpke +6

Scientific workflows process extensive data sets over clusters of independent nodes, which requires a complex stack of infrastructure components, especially a resource manager (RM)…

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…

cs.DC2024★ 1 cited

Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows

Rafael Ferreira da Silva, Deborah Bard, Kyle Chard +108

The Workflows Community Summit gathered 111 participants from 18 countries to discuss emerging trends and challenges in scientific workflows, focusing on six key areas: time-sensit…

cs.DC2024★ 1 cited

Ponder: Online Prediction of Task Memory Requirements for Scientific Workflows

Fabian Lehmann, Jonathan Bader, Ninon De Mecquenem +5

Scientific workflows are used to analyze large amounts of data. These workflows comprise numerous tasks, many of which are executed repeatedly, running the same custom program on d…

cs.DC2024★ 9 cited

Sizey: Memory-Efficient Execution of Scientific Workflow Tasks

Jonathan Bader, Fabian Skalski, Fabian Lehmann +4

As the amount of available data continues to grow in fields as diverse as bioinformatics, physics, and remote sensing, the importance of scientific workflows in the design and impl…

cs.DC2024★ 2 cited

Scaling on Frontier: Uncertainty Quantification Workflow Applications using ExaWorks to Enable Full System Utilization

Mikhail Titov, Robert Carson, Matthew Rolchigo +6

When running at scale, modern scientific workflows require middleware to handle allocated resources, distribute computing payloads and guarantee a resilient execution. While indivi…

cs.DC2023★ 2 cited

The Common Workflow Scheduler Interface: Status Quo and Future Plans

Fabian Lehmann, Jonathan Bader, Lauritz Thamsen +1

Nowadays, many scientific workflows from different domains, such as Remote Sensing, Astronomy, and Bioinformatics, are executed on large computing infrastructures managed by resour…

cs.DC2023★ 11 cited

Large Language Models to the Rescue: Reducing the Complexity in Scientific Workflow Development Using ChatGPT

Mario Sänger, Ninon De Mecquenem, Katarzyna Ewa Lewińska +4

Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability,…

cs.DC2023★ 17 cited

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…

cs.DC2023★ 1 cited

Validity Constraints for Data Analysis Workflows

Florian Schintke, Ninon De Mecquenem, David Frantz +9

Porting a scientific data analysis workflow (DAW) to a cluster infrastructure, a new software stack, or even only a new dataset with some notably different properties is often chal…

cs.DC2023

Workflows Community Summit 2022: A Roadmap Revolution

Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala +102

Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex s…

cs.DC2023★ 13 cited

How Workflow Engines Should Talk to Resource Managers: A Proposal for a Common Workflow Scheduling Interface

Fabian Lehmann, Jonathan Bader, Friedrich Tschirpke +2

Scientific workflow management systems (SWMSs) and resource managers together ensure that tasks are scheduled on provisioned resources so that all dependencies are obeyed, and some…

cs.DC2022★ 7 cited

Towards Advanced Monitoring for Scientific Workflows

Jonathan Bader, Joel Witzke, Soeren Becker +5

Scientific workflows consist of thousands of highly parallelized tasks executed in a distributed environment involving many components. Automatic tracing and investigation of the c…

cs.DC2022★ 10 cited

Reshi: Recommending Resources for Scientific Workflow Tasks on Heterogeneous Infrastructures

Jonathan Bader, Fabian Lehmann, Alexander Groth +5

Scientific workflows typically comprise a multitude of different processing steps which often are executed in parallel on different partitions of the input data. These executions,…

cs.DC2022★ 20 cited

Lotaru: Locally Estimating Runtimes of Scientific Workflow Tasks in Heterogeneous Clusters

Jonathan Bader, Fabian Lehmann, Lauritz Thamsen +3

Many scientific workflow scheduling algorithms need to be informed about task runtimes a-priori to conduct efficient scheduling. In heterogeneous cluster infrastructures, this prob…