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Changes between Version 15 and Version 16 of cypress/R

Timestamp:: 08/22/18 19:06:05 (6 years ago)
Author:: cbaribault
Comment:: CEB 20180822 - Fixed R package dependency error, clarified workflow in general.

Legend:

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: Added
: Removed
: Modified

cypress/R

-              v15
+              v16
 {{{
 [tulaneID@cypress01-035 pp-1.6.4]$ module load R/3.1.2
+[tulaneID@cypress01-035 pp-1.6.4]$ module load R/3.2.4
 [tulaneID@cypress01-035 pp-1.6.4]$ module list
 Currently Loaded Modulefiles:
 ) git/2.4.1           3) idev                5) R/3.1.2
+) git/2.4.1           3) idev                5) R/3.2.4
 ) slurm/14.03.0       4) bbcp/amd64_rhel60
 }}}
 …
 [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 version 3.2.4 (2016-03-10) -- "Very Secure Dishes"
+Copyright (C) 2016 The R Foundation for Statistical Computing
+Platform: x86_64-pc-linux-gnu (64-bit)
 R is free software and comes with ABSOLUTELY NO WARRANTY.
 …
 Type 'q()' to quit R.
+>
+>
 }}}
 …
 #SBATCH --cpus-per-task=1       # Number of threads per task (OMP threads)
 module load R/3.1.2
+module load R/3.2.4
 Rscript myRscript.R
 }}}
+'''For Workshop''' :
+If you use a temporary workshop account, modify the SLURM script like:
+{{{#!bash
+#!/bin/bash
+#SBATCH --partition=workshop    # Partition
+#SBATCH --qos=workshop          # Quality of Service
+##SBATCH --qos=normal          ### Quality of Service (like a queue in PBS)
+#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/3.2.4
+Rscript myRscript.R
+}}}
 == Running a Parallel R Job ==
 Starting with version 2.14.0, R has offered direct support for parallel computation through the "parallel" package. We will present two examples of running a parallel job of BATCH mode. They differ in the ways in which they communicate the number of cores reserved by SLURM to R. Both are based on code found in [https://cran.r-project.org/web/packages/doParallel/vignettes/gettingstartedParallel.pdf "Getting Started with doParallel and foreach" by Steve Weston and Rich Calaway] and modified by [https://rcc.uchicago.edu/docs/software/environments/R/index.html The University of Chicago Resource Computing Center].
+In the first example, we will use the built in R function '''Sys.getenv( )''' to get the SLURM environment variable from the operating system.
+=== Passing (SLURM) Environment Variables ===
+In the first example, we will use the built in R function '''Sys.getenv( )''' to get the SLURM environment variable from the operating system.
+Edit the new file '''bootstrap.R''' to contain the following code.
 {{{#!r
 …
 }}}
 This script will obtain the number of tasks per node set in our SLURM script and will pass that value to the '''registerDoParallel( )''' function. To implement this we need only set the correct parameters in our SLURM script. Suppose we wanted to use 16 cores. Then the correct script would be
+The above script will obtain the number of tasks per node via the SLURM environment variable '''SLURM_CPUS_PER_TASK''' set in our SLURM script and will pass that value to the '''registerDoParallel( )''' function. To implement this we need only set the correct parameters in our SLURM script. Suppose we wanted to use 16 cores. Then the correct SLURM script would be as follows.
 {{{#!bash
 …
 #SBATCH --cpus-per-task=16      # Number of threads per task (OMP threads)
+module load R/3.1.2
+Rscript bootstrap.R $SLURM_CPUS_PER_TASK
+}}}
+The disadvantage of this approach is that it is system specific. If we move our code to a machine that uses PBS-Torque as it's manager (sphynx for example) we have to change our source code. An alternative method that results in a more portable code base uses command line arguments to pass the value of our environment variables into the script.
+module load R/3.2.4
+Rscript bootstrap.R
+}}}
+'''For Workshop''' :
+If you use a temporary workshop account, modify the SLURM script like:
+{{{#!bash
+#!/bin/bash
+#SBATCH --partition=workshop    # Partition
+#SBATCH --qos=workshop          # Quality of Service
+##SBATCH --qos=normal          ### Quality of Service (like a queue in PBS)
+#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 per Node
+#SBATCH --cpus-per-task=16      # Number of threads per task (OMP threads)
+module load R/3.2.4
+Rscript bootstrap.R
+}}}
+Edit the new file '''bootstrap.sh''' to contain the above SLURM script code.
+=== R Package Dependency ===
+So, for example, in order to run the above, we would submit the above SLURM script via '''sbatch''' command, but in general we would not expect this code to run the very first time with out additional setup.  We can try running the above scripts thus far without any additional setup, but we can expect to get the error such as in the following R session.
+{{{#!r
+> library(doParallel)
+Error in library(doParallel) : there is no package called ‘doParallel’
+}}}
+Thus we should first ensure that the required R package, in this case the R package '''doParallel''', is available and installed in your environment. For a range of options for installing R packages - depending on the desired level of reproducibility, see the section [#InstallingRPackages Installing R Packages on Cypress].
+'''For Workshop''' :
+If you use a temporary workshop account, use [#RPackageAlternative1 Alternative 1] for installing R packages.
+Once we have resolved our package dependencies, we now expect the job to run without errors.
+Also, note that since we did not specify an output file in the SLURM script, the output will be written to slurm-<!JobNumber>.out. For example:
+{{{
+[tulaneID@cypress2 R]$ sbatch bootstrap.sh
+Submitted batch job 774081
+[tulaneID@cypress2 R]$ cat slurm-774081.out
+Loading required package: foreach
+Loading required package: iterators
+Loading required package: parallel
+[1] "16"
+elapsed
+.954
+[tulaneID@cypress2 R]$
+}}}
+=== Passing Parameters ===
+The disadvantage of the above approach is that it is system specific. If we move our code to a machine that uses PBS-Torque as it's manager (sphynx for example) we have to change our source code. An alternative method that results in a more portable code base uses command line arguments to pass the value of our environment variables into the script.
+Edit the new file '''bootstrapWargs.R''' to contain the following code.
 {{{#!r
 …
 #SBATCH --cpus-per-task=16      # Number of threads per task (OMP threads)
 module load R/3.1.2
+module load R/3.2.4
 Rscript bootstrapWargs.R $SLURM_CPUS_PER_TASK
 }}}
+Not that since we did not specify an output file, the output will be written to slurm-<!JobNumber>.out. For example:
+{{{
+[cmaggio@cypress1 ~]$ sbatch RsubmissionWargs.srun
+'''For Workshop''' :
+If you use a temporary workshop account, modify the SLURM script like:
+{{{#!bash
+#!/bin/bash
+#SBATCH --partition=workshop    # Partition
+#SBATCH --qos=workshop          # Quality of Service
+##SBATCH --qos=normal          ### Quality of Service (like a queue in PBS)
+#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 per Node
+#SBATCH --cpus-per-task=16      # Number of threads per task (OMP threads)
+module load R/3.2.4
+Rscript bootstrapWargs.R $SLURM_CPUS_PER_TASK
+}}}
+Edit the new file '''bootstrapWargs.sh''' to contain the above SLURM script code.
+Now submit as in the following.
+{{{
+[tulaneID@cypress1 ~]$ sbatch bootstrapWargs.sh
 Submitted batch job 52481
 [tulaneID@cypress1 ~]$ cat slurm-52481.out
 …
 == Installing R Packages into user home directory or lustre sub-directory ==
+== [=#InstallingRPackages Installing R Packages on Cypress] ==
 If you want to use some R packages that are not yet installed in your desired version of R on Cypress,
 then you have several alternatives - depending on your desired level of reproducibility.
 === Alternative 1 - default to home sub-directory ===
+then you have several alternatives, as prescribed below, for locations for installing those packages. Those locations include either your user home directory or lustre sub-directory, and the methods will vary depending on your desired level of reproducibility.
+=== [=#RPackageAlternative1 Alternative 1] - default to home sub-directory ===
 From your R session, you may choose to have R install its packages into a sub-directory under your home directory.
 By default R will create such a sub-directory whose name corresponds to the R version of your current R session and install your packages there.
 …
 ~/R/x86_64-pc-linux-gnu-library/3.4
 to install packages into?  (y/n) y
+...
+}}}
+--- Please select a CRAN mirror for use in this session ---
+PuTTY X11 proxy: unable to connect to forwarded X server: Network error: Connection refused
+HTTPS CRAN mirror
+: 0-Cloud [https]                   2: Algeria [https]
+...
+: Vietnam [https]                  80: (HTTP mirrors)
+Selection: 77
+...
+}}}
+Note that the above example was performed without X11 forwarding, resulting in a prompt at the command line for selection of a CRAN mirror site in the above, at which point you should enter the number corresponding to the desired mirror site, e.g. '''77'''.
 === Alternative 2 - specify your lustre sub-directory via exported environment variable ===