Fast implementation of survival analysis models (CoxPH, WCE...) with GPU support, for R and Python. Please note that this package is still little more than a proof of concept: we are working to publish a first stable version by the summer of 2023. We have opened the code to get a first feed back from the community, but stress that our solver has not yet been tested thoroughly. The user interface of the Python and R packages are also likely to change over the next few months.
If you find this work useful, please cite:
Accélération des calculs à l'aide de cartes graphiques pour la détection de signaux de pharmacovigilance sur le Système national des données de santé : le package survivalGPU, A. Van Straaten, P. Sabatier, J. Feydy, A-S. Jannot, Revue d'Épidémiologie et de Santé Publique, Volume 71, Supplement 1, 2023, 101467, ISSN 0398-7620, https://doi.org/10.1016/j.respe.2023.101467.
For the Python survivalgpu package, go to the survivalGPU/python folder and run pytest .
For the R survivalGPU package, go to the survivalGPU/R folder. Then, launch an R interactive session and run:
library(devtools)
load_all()
test()
# To render the documentation as a static website:
pkgdown::build_site()
