Publications and Open-Source Software
Papers and open-source software resulting from our research:
📄 A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows
Future Generation Computer Systems, 2026
In this study, we first quantify the problem of carbon emissions associated with running scientific workflows, and then demonstrate the transformative potential for carbon-aware workflow execution. We estimate the carbon footprint of seven real-world Nextflow workflows executed on diverse dedicated cluster and public cloud resources using high-resolution average and marginal grid carbon intensity data from open and commercial data providers. Furthermore, we conduct a systematic evaluation of the impact of carbon-aware temporal shifting, and the dynamic pausing and resuming of the workflow. Moreover, we investigate the impact of resource scaling at both workflow and workflow task levels. Finally, we report substantial potential reductions in overall carbon emissions, with temporal shifting capable of decreasing emissions by over 80%, and resource scaling by 67%.
📄 Energy-Aware Workflow Execution: An Overview of Techniques for Saving Energy and Emissions in Scientific Compute Clusters
To appear in a textbook on Workflow Systems for Large-Scale Scientific Data Analysis, 2025
Scientific research in many fields routinely requires the analysis of large datasets, and scientists often employ workflow systems to leverage clusters of computers for their data analysis. However, due to their size and scale, these workflow applications can have a considerable environmental footprint in terms of compute resource use, energy consumption, and carbon emissions. Mitigating this is critical in light of climate change and the urgent need to reduce carbon emissions.
📄 Ichnos: A Carbon Footprint Estimator for Scientific Workflows
To appear in the Post-Proceedings of the 1st International Workshop on Low Carbon Computing (LOCO), 2025
In this paper, we introduce a system to estimate the carbon footprint of Nextflow scientific workflows that enables post-hoc estimation based on existing workflow traces, power models for computational resources utilised, and carbon intensity data aligned with the execution time.
📄 Exploring the Potential of Carbon-Aware Execution for Scientific Workflows
In the Proceedings of the 25th IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2025
In this short paper, we demonstrate the potential for carbon-aware workflow execution. For this, we estimate the carbon footprint of two real-world Nextflow workflows executed on cluster infrastructure and evaluate the impact of carbon-aware temporal shifting, pausing and resuming, and resource scaling.
💻 Ichnos software for Carbon Footprint Estimation for Scientific Workflows
A project with scripts to methodically calculate the carbon footprint of workflow executions from Nextflow trace files, using power models and carbon intensity data.