In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The 'crew.cluster' package extends the 'mirai'-powered 'crew' package with worker launcher plugins for traditional high-performance computing systems. Inspiration also comes from packages 'mirai' by Gao (2023) <https://github.com/shikokuchuo/mirai>, 'future' by Bengtsson (2021) <doi:10.32614/RJ-2021-048>, 'rrq' by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>, 'clustermq' by Schubert (2019) <doi:10.1093/bioinformatics/btz284>), and 'batchtools' by Lang, Bischl, and Surmann (2017). <doi:10.21105/joss.00135>.
[email protected] is safe to use (health: 46/100)
Get this data programmatically — free, no authentication.
curl https://depscope.dev/api/check/conda/r-crew.clusterFirst published · 2024-02-23 19:11:54.484000+00:00
Last updated · 2025-09-21 11:25:45.145000+00:00