An R package to deploy h2o on the Harvard Odyssey cluster
Create the folder apps/R
in your home folder
mkdir apps mkdir apps/R
Modify your .bashrc
file as follows:
# .bashrc # Source global definitions if [ -f /etc/bashrc ]; then . /etc/bashrc fi # User specific aliases and functions source new-modules.sh module load R # replace username with your username. You may have to change home03 too. export R_LIBS_USER=/n/home03/username/apps/R:$R_LIBS_USER
h2odyssey
In an R session:
devtools::install_github("NSAPH/h2odyssey")
h2odyssey
on Harvard OdysseyYou first need to start a SLURM job.
# Example: we request a total of 2GB on 2 nodes with 20 cores per node in the shared partition # srun -p shared --mem 2g -t 0-06:00 -c 20 -N 2 --pty /bin/bash # Example: we request a total of 300GB on 2 nodes with 32 cores per node in the bigmem partition # srun -p bigmem --pty --mem 300g -t 0-06:00 -c 32 -N 2 /bin/bash
screen
To use screen
:
# srun -p shared --pty --mem 2g -t 0-06:00 -c 20 -N 2 R
From a compute node:
library(h2odyssey) # memory per node in GB # start and connect to an h2o cluster with 2GB of RAM per node start_h2o_cluster(memory = 2) # Code here... h2o.shutdown()
You can try h2o examples:
https://github.com/h2oai/h2o-tutorials/blob/master/h2o-open-tour-2016/chicago/intro-to-h2o.R
https://github.com/h2oai/h2o-tutorials/blob/master/tutorials/ensembles-stacking/stacked_ensemble_h2o_xgboost.Rmd
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