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habrok:examples:r [2021/03/02 12:44] – external edit 127.0.0.1habrok:examples:r [2023/03/22 13:29] (current) – [Multiple nodes] fokke
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 #SBATCH --mem=1000 #SBATCH --mem=1000
  
-ml R/3.4.4-foss-2018a-X11-20180131+module purge 
 +module load R/4.2.1-foss-2022a
 Rscript R_example1.R Rscript R_example1.R
 </code> </code>
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 #SBATCH --mem=10GB #SBATCH --mem=10GB
  
-module load R/3.4.4-foss-2018a-X11-20180131+module purge 
 +module load R/4.2.1-foss-2022a
  
 Rscript parallel.R Rscript parallel.R
 </code> </code>
  
-The file containing the R code is named ''%%parallel.R%%''. Note that the package ''%%parallel%%'' and ''%%snow%%'' are used but others might be available as well. If necessary additional packages have to be installed, see [[peregrine:software_environment:installation_of_extra_applications_or_libraries#r|this page]].+The file containing the R code is named ''%%parallel.R%%''. Note that the package ''%%parallel%%'' and ''%%snow%%'' are used but others might be available as well. If necessary additional packages have to be installed, see [[habrok:software_environment:installation_of_extra_applications_or_libraries#r|this page]].
  
 <code r parallel.R> <code r parallel.R>
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 #SBATCH --mem=10GB #SBATCH --mem=10GB
  
-module load R/3.4.4-foss-2018a-X11-20180131+module purge 
 +module load R/4.2.1-foss-2022a
  
 srun ${EBROOTR}/lib64/R/library/snow/RMPISNOW < parallel.R srun ${EBROOTR}/lib64/R/library/snow/RMPISNOW < parallel.R
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 ==== GPU ==== ==== GPU ====
  
-In order to let R use the GPUs of the Peregrine cluster, we first have install the R library ''gpuR''. Unfortunately, this library has been removed from CRAN, and we will need to install it from GitHub. To do this, we first start an interactive job on one of the GPU nodes with an NVidia V100 GPU. You can similarly install it from a node with an NVidia K40 GPU, but we have fewer of those. This is how you start an interactive job from the command line on the login node:+In order to let R use the GPUs of the Hábrók cluster, we first have install the R library ''gpuR''. Unfortunately, this library has been removed from CRAN, and we will need to install it from GitHub. To do this, we first start an interactive job on one of the GPU nodes with an NVidia V100 GPU. You can similarly install it from a node with an NVidia K40 GPU, but we have fewer of those. This is how you start an interactive job from the command line on the login node:
 <code bash> <code bash>
 srun --time=00:30:00 --partition=gpushort --gres=gpu:v100:1 --cpus-per-task=12 --pty bash -i srun --time=00:30:00 --partition=gpushort --gres=gpu:v100:1 --cpus-per-task=12 --pty bash -i
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 Now we can submit the job using ''%%sbatch gpuExampleR.sh%%''.\\ Now we can submit the job using ''%%sbatch gpuExampleR.sh%%''.\\
 In this example the matrix multiplication is slower for the GPU when small matrices are used (100x100); however, as the matrix gets larger, the GPU speed will scale better as can be seen from the output. In this example the matrix multiplication is slower for the GPU when small matrices are used (100x100); however, as the matrix gets larger, the GPU speed will scale better as can be seen from the output.
 +
 +===== Installing additional R libraries =====
 +
 +R provides the ''install.packages'' command to install additional libraries/packages. Before you start submitting jobs, you can use it to install the packages that you need in the following way:
 +
 +  * log in and load the R module that you would like to use, e.g.: ''module load R/4.2.1-foss-2022a''
 +  * launch R by running the command: ''R''
 +  * run the appropriate ''install.packages'' command for all packages that you want to install. The first time you will do this, R will ask you permission to create a personal library installation directory in your home directory.
 +  * quit using ''q()''
 +
 +Now the packages will be available for any job that you run. Note that you do have to do this again once you switch to a completely different R version.
 +
 +==== Login node limits ====
 +
 +Note that if you are trying to install something on the login node, you may run into certain limits that prevent you from using too much memory on the login node. See [[:habrok:additional_information:faq#i_am_running_something_on_the_login_node_and_the_process_gets_killed_why_does_this_happen|this]] question in the FAQ for more information.
  
 ===== Useful packages ===== ===== Useful packages =====
  
-One of our Peregrine users has developed an R package to send function calls as jobs on Slurm via SSH. You can find the documentation and installation instructions on [[https://github.com/mschubert/clustermq|this]] GitHub Page.+One of our users has developed an R package to send function calls as jobs on Slurm via SSH. You can find the documentation and installation instructions on [[https://github.com/mschubert/clustermq|this]] GitHub Page.