BwUniCluster2.0/Software/R/Rstan

General information

rstan provides the R interface for Stan, a platform for statistical modeling and high-performance statistical computation.

To be compatible with our R installation, we recommend to install the development version of rstan.

Installation

Please enter the following code, presented in the boxes below, directly in your shell/command line on bwUniCluster

Preparations

Prepare .R directory (if it does not already exists). This is then filled with information how R should compile the packages ('compilation flags'). These are written (and can be reviewed) into the (text) file Makevars.

If you already have a .R/Makevars file, check whether these flags are already set.

cat ~/.R/Makevars

In this case, skip the following block of five commands. If this is not the case, enter the following commands in your shell (command line).

mkdir -p ~/.R
echo "CXX14=icpc" >> ~/.R/Makevars
echo "CXX14FLAGS=-O3 -fPIC -std=c++14 -wd308 -axCORE-AVX512,CORE-AVX2,AVX -xSSE4.2 -fp-model strict -qopenmp" >> ~/.R/Makevars
echo "CXXFLAGS += -std=c++14 -wd308" >> ~/.R/Makevars
echo "PKG_CXXFLAGS += -std=c++14 -wd308" >> ~/.R/Makevars

The installation of rstan and its dependencies makes use other libraries (TBB, Threading Building Blocks) which need to be loaded before installation (and R, of course).

module purge 	
module load math/R/4.1.2
module load devel/tbb/2021.4.0

The installation process of rstan and its dependencies (Rcpp) needs input of how to use the TBB module. This is provided via specific environment variables. We also need to provide a further configuration information to install the R package v8 rstan depends on.

export TBB_LIB=$TBB_LIB_DIR
export TBB_INC=$TBB_INC_DIR
export TBB_INTERFACE_NEW='true'
export DOWNLOAD_STATIC_LIBV8=1

Installing the R package(s) [takes roughly 20 min]

We can now install rstan (in its development version) and its dependencies within a R session

Consider starting an interactive job for compiling. You need at most 5000MB total memory, e.g. start

salloc -t 30 -n 1 --mem=5000 -p dev_single 

Now, start R and install

R -q
> install.packages("remotes")
> install.packages("RcppParallel")
> install.packages("V8")
> remotes::install_github("hsbadr/rstan/StanHeaders@develop", force = TRUE)
> remotes::install_github("hsbadr/rstan/rstan/rstan@develop", force = TRUE)

Testing the installation

To check whether the installation worked, make a test run in R

> library(rstan)
> example(stan_model, package = "rstan", run.dontrun = TRUE)

Preparations to use the rstan package

To run its applications, rstan compiles new scripts. For this, it again uses TBB, so you need to set the corresponding environment variables whenever you use rstan - as well as to load the R and TBB modules.

For this, we recommend to add the modules

module load math/R/4.1.2
module load devel/tbb/2021.4.0

as well as the three export commands

export TBB_LIB=$TBB_LIB_DIR
export TBB_INC=$TBB_INC_DIR
export TBB_INTERFACE_NEW='true'

to your batch job scripts that use rstan or to run them directly in the command line if you use an interactive session.

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