If using resources on this website, please cite:
Lannelongue, L., Grealey, J., Inouye, M., Green Algorithms: Quantifying the Carbon Footprint of Computation. Adv. Sci. 2021, 8, 2100707. https://doi.org/10.1002/advs.202100707
All publications related to the Green Algorithms project:
2023
- L. Lannelongue and M. Inouye, ‘Carbon footprint estimation for computational research’, Nat Rev Methods Primers, vol. 3, no. 1, Art. no. 1, Feb. 2023, doi: 10.1038/s43586-023-00202-5. [pdf]
2022
- L. Grealey, L. Lannelongue., W.-Y. Saw, J. Marten, G. Méric, S. Ruiz-Carmona and M. Inouye, ‘The Carbon Footprint of Bioinformatics’, Molecular Biology and Evolution, p. msac034, Feb. 2022, doi: 10.1093/molbev/msac034. [pdf]
- L. Lannelongue, ‘Carbon footprint: the (not so) hidden cost of high performance computing’, ITNOW, vol. 63, no. 4, pp. 12–13, Jan. 2022, doi: 10.1093/itnow/bwab100. [pdf]
2021
- L. Lannelongue, J. Grealey, and M. Inouye, ‘Green Algorithms: Quantifying the Carbon Footprint of Computation’, Advanced Science, vol. 8, no. 12, p. 2100707, July 2021, doi: 10.1002/advs.202100707. [pdf]
- L. Lannelongue, J. Grealey, A. Bateman, and M. Inouye, ‘Ten simple rules to make your computing more environmentally sustainable’, PLoS Computational Biology, vol. 17, no. 9, p. e1009324, Sept. 2021, doi: 10.1371/journal.pcbi.1009324. [pdf]
2020
- M. Inouye, L. Lannelongue and J. Grealey, Green Algorithms for Health Data Science, HDR UK Blog, Mar. 2020.