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
- ‘GREENER principles for environmentally sustainable computational science’, L. Lannelongue, H.-E. G. Aronson, A. Bateman, E. Birney, T. Caplan, M. Juckes, J. McEntyre, A. D. Morris, G. Reilly and M. Inouye, Nat Comput Sci, vol. 3, no. 6, pp. 514–521, Jun. 2023, doi: 10.1038/s43588-023-00461-y. [pdf]
- ‘Carbon footprint estimation for computational research’, L. Lannelongue and M. Inouye, Nat Rev Methods Primers, vol. 3, no. 1, Art. no. 1, Feb. 2023, doi: 10.1038/s43586-023-00202-5. [pdf]
2022
- ‘The Carbon Footprint of Bioinformatics’, L. Grealey, L. Lannelongue., W.-Y. Saw, J. Marten, G. Méric, S. Ruiz-Carmona and M. Inouye, Molecular Biology and Evolution, p. msac034, Feb. 2022, doi: 10.1093/molbev/msac034. [pdf]
- ‘Carbon footprint: the (not so) hidden cost of high performance computing’, L. Lannelongue, ITNOW, vol. 63, no. 4, pp. 12–13, Jan. 2022, doi: 10.1093/itnow/bwab100. [pdf]
2021
- ‘Green Algorithms: Quantifying the Carbon Footprint of Computation’, L. Lannelongue, J. Grealey, and M. Inouye, Advanced Science, vol. 8, no. 12, p. 2100707, July 2021, doi: 10.1002/advs.202100707. [pdf]
- ‘Ten simple rules to make your computing more environmentally sustainable’, L. Lannelongue, J. Grealey, A. Bateman, and M. Inouye, PLoS Computational Biology, vol. 17, no. 9, p. e1009324, Sept. 2021, doi: 10.1371/journal.pcbi.1009324. [pdf]
2020
- Green Algorithms for Health Data Science, M. Inouye, L. Lannelongue and J. Grealey, HDR UK Blog, Mar. 2020.