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
Official Project Start
February 10, 2025
We are pleased to announce the official start of the EPSRC-funded Casper project, aiming to provide valuable insights into carbon-aware computing to tackle the challenge of aligning flexible cloud computing with low-carbon energy availability.
Read moreRecent Publications and Open-Source Software
Exploring the Potential of Carbon-Aware Execution for Scientific Workflows
Kathleen West, Fabian Lehmann, Vasilis Bountris, Ulf Leser, Yehia Elkhatib, and Lauritz Thamsen
To appear in the Proceedings of the 25th IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2025
Ichnos: A Carbon Footprint Estimator for Scientific Workflows
Kathleen West, Yehia Elkhatib, and Lauritz Thamsen