wiki:cypress/R

Version 1 (modified by cmaggio, 6 years ago) (diff)

Running R on Cypress

Python Modules

As of August 18th, 2015 there is one version of R installed on Cypress in the module

  • R/3.1.2

Installing Packages

Running R Interactively

Start an interactive session using idev

[tulaneID@cypress1 pp-1.6.4]$ idev 
Requesting 1 node(s)  task(s) to normal queue of defq partition
1 task(s)/node, 20 cpu(s)/task, 2 MIC device(s)/node
Time: 0 (hr) 60 (min).
Submitted batch job 52311
Seems your requst is pending.
JOBID=52311 begin on cypress01-035
--> Creating interactive terminal session (login) on node cypress01-035.
--> You have 0 (hr) 60 (min).
[tulaneID@cypress01-035 pp-1.6.4]$ 

Load the R module

[tulaneID@cypress01-035 pp-1.6.4]$ module load R/3.1.2
[tulaneID@cypress01-035 pp-1.6.4]$ module list
Currently Loaded Modulefiles:
  1) git/2.4.1           3) idev                5) R/3.1.2
  2) slurm/14.03.0       4) bbcp/amd64_rhel60

Run R in the command line window

[tulaneID@cypress01-035 pp-1.6.4]$R

R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: x86_64-unknown-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> 

Running a R script in Batch mode

You can also submit your Python job to the batch nodes (compute nodes) on Cypress. Inside your SLURM script, include a command to load the desired Python module. Then invoke python on your python script.

#!/bin/bash
#SBATCH --qos=workshop          # Quality of Service
#SBATCH --partition=workshop    # Partition
#SBATCH --job-name=R            # Job Name
#SBATCH --time=00:01:00         # WallTime
#SBATCH --nodes=1               # Number of Nodes
#SBATCH --ntasks-per-node=1     # Number of tasks (MPI processes)
#SBATCH --cpus-per-task=1       # Number of threads per task (OMP threads)

module load R/3.1.2
python myRscript.py

Running a Parallel R Job