Casper: Carbon-Aware Scalable Processing in Elastic Clusters
The Casper project investigates how the execution of scalable batch processing applications can be aligned with the availability of low-carbon energy. More specifically, we aim to pioneer how individual processing steps of large-scale cluster applications can be managed dynamically based on continuously updated estimates of application performance, resource availability, and carbon intensity.
About Our Research
The three main goals towards our project aim are:
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Develop the methods needed to reliably reduce the emissions of large scalable batch data processing applications on elastic compute clusters significantly
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Design and implement a prototype for elastic Kubernetes clusters and scalable batch data processing (such as Nextflow workflows and Spark dataflows)
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Evaluate the prototype system in use cases covering (1) a commercial cluster service of a leading public cloud provider and (2) a similar service running on the private cloud resources of a research organisation
Latest News
New preprint presenting the Ichnos+ workflow footprint estimator
July 16, 2026
A new preprint detailing Ichnos+, a system for estimating the environmental footprint of scientific workflows using fitted power models, is up on arXiv.
Read moreIEEE CLOUD 2026 research paper on workflow energy prediction
June 11, 2026
Our full conference paper on Augur predicts workflow energy consumption before execution and was accepted for IEEE CLOUD 2026.
Read moreFuture Generation Computer Systems article on carbon-aware scientific workflows
March 06, 2026
Our journal article “A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows” has been published in Elsevier's FGCS journal.
Read moreRecent Publications and Open-Source Software
Augur: Pre-Execution Energy Prediction for Workflow Tasks in Heterogeneous Clusters
Kathleen West, Vasilis Bountris, Philipp Thamm, Ulf Leser, Yehia Elkhatib, and Lauritz Thamsen
To appear in the Proceedings of the 19th IEEE International Conference on Cloud Computing (CLOUD), 2026
Energy-Aware Workflow Execution: An Overview of Techniques for Saving Energy and Emissions in Scientific Compute Clusters
Lauritz Thamsen, Yehia Elkhatib, Paul Harvey, Syed Waqar Nabi, Jeremy Singer, and Wim Vanderbauwhede
Workflow Systems for Large-Scale Scientific Data Analysis, 2026
A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows
Kathleen West, Youssef Moawad, Fabian Lehmann, Vasilis Bountris, Ulf Leser, Yehia Elkhatib, Lauritz Thamsen
Future Generation Computer Systems, 2026