We are happy to share that our full workshop paper on “Ichnos: A Carbon Footprint Estimator for Scientific Workflows” has been accepted for publication in the post-proceedings of the 1st International Workshop on Low Carbon Computing (LOCO 2024), which was held as a hybrid event in Glasgow on December 3rd last year.

In the paper, we present a new 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. We also discuss our automated power modelling approach, and compare it with commonly used estimation methodologies. Finally, we exemplify several potential use cases and evaluate our energy consumption estimation approach, finding its estimation error to be between 3.9–10.3% and lower than baseline methodologies.

While we are still preparing the final camera-ready full workshop paper to share it as soon as we can, you can already have a look at the extended abstract on arXiv, the talk recording on YouTube, and the open-source code on GitHub.