BwUniCluster2.0/Software/R/Rstan: Difference between revisions
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= General information = |
= General information = |
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rstan provides the R interface for [https://mc-stan.org/ Stan], a platform for statistical modeling and high-performance statistical computation. |
<code>rstan</code> provides the R interface for [https://mc-stan.org/ Stan], a platform for statistical modeling and high-performance statistical computation. |
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To be compatible with our R installation, we recommend to install the development version of rstan. |
To be compatible with our R installation, we recommend to install the development version of rstan. |
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= Installation = |
= Installation instructions = |
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Please enter the following code, presented in the boxes below, directly |
Please enter the following code, presented in the boxes below, directly in your shell/command line on '''bwUniCluster2.0'''. |
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== Preparations == |
== Preparations == |
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Installing <code>glmnet</code> involves compiling source code. Therefore, ensure that the following flags are set in <code>$HOME/.R/Makevars</code>: |
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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. |
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If you already have a .R/Makevars file, check whether these flags are already set. |
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<pre> |
<pre> |
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cat ~/.R/Makevars |
cat ~/.R/Makevars |
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CXX14=g++ |
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CXX17=g++ |
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CXX14FLAGS += -std=c++14 |
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CXX17FLAGS += -std=c++17 |
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CXXFLAGS = -O3 -fPIC -march=cascadelake -ffp-contract=off -fno-fast-math -fno-signed-zeros -fopenmp -Wno-unknown-warning-option |
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</pre> |
</pre> |
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If necessary, the appropriate compiler flags can be set by running the following lines of code: |
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In this case, skip the following five command block |
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<pre> |
<pre> |
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mkdir -p ~/.R |
mkdir -p ~/.R |
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echo "CXX14= |
echo "CXX14=g++" > ~/.R/Makevars |
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echo " |
echo "CXX17=g++" >> ~/.R/Makevars |
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echo "CXXFLAGS |
echo "CXXFLAGS = -O3 -fPIC -march=cascadelake -ffp-contract=off -fno-fast-math -fno-signed-zeros -fopenmp -Wno-unknown-warning-option" >> ~/.R/Makevars |
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echo " |
echo "CXX14FLAGS += -std=c++14" >> ~/.R/Makevars |
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echo "CXX17FLAGS += -std=c++17" >> ~/.R/Makevars |
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</pre> |
</pre> |
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Since installing <code>glmnet</code> involves compiling, we start an <b>interactive session</b> on one of the compute nodes: |
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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). |
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<pre> |
<pre> |
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| ⚫ | |||
module purge |
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module load devel/tbb/2021.4.0 |
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</pre> |
</pre> |
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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. |
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Within the interactive session, load the R 4.4.1 module and provide configuration information to install the R package <code>v8</code>, rstan depends on. |
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<pre> |
<pre> |
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# Load the R software module: |
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export TBB_LIB=$TBB_LIB_DIR |
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| ⚫ | |||
export TBB_INC=$TBB_INC_DIR |
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export TBB_INTERFACE_NEW='true' |
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# Provide configuration information for the v8 R package |
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export DOWNLOAD_STATIC_LIBV8=1 |
export DOWNLOAD_STATIC_LIBV8=1 |
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</pre> |
</pre> |
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== Installing the R package(s) [takes roughly 20 min] == |
== Installing the R package(s) [takes roughly 20 min] == |
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Now, start <code>R</code> and install <code>RStan</code> using the lines of code below: |
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We can now install rstan (in its development version) and its dependencies within a R session |
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Consider starting an interactive job for compiling. You need at least 5000MB total memory, e.g. start |
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<pre> |
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| ⚫ | |||
</pre> |
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Now, start R and install |
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<pre> |
<pre> |
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</pre> |
</pre> |
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== Testing the installation == |
== Testing the installation == |
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To check whether the installation worked, make a test run in R |
To check whether the installation worked, make a test run in R |
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> example(stan_model, package = "rstan", run.dontrun = TRUE) |
> example(stan_model, package = "rstan", run.dontrun = TRUE) |
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</pre> |
</pre> |
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= Preparations to use the rstan package = |
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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. |
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For this, we recommend to add the modules |
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<pre> |
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module load math/R/4.1.2 |
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module load devel/tbb/2021.4.0 |
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</pre> |
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as well as the three export commands |
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<pre> |
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export TBB_LIB=$TBB_LIB_DIR |
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export TBB_INC=$TBB_INC_DIR |
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export TBB_INTERFACE_NEW='true' |
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</pre> |
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to your [[BwUniCluster_2.0_Slurm_common_Features#sbatch_Examples | batch job scripts]] that use rstan or to run them directly in the command line if you use an [[BwUniCluster_2.0_Batch_Queues | interactive session]]. |
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---- |
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[[Category:BwUniCluster]] |
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[[Category:BwUniCluster_2.0]] |
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Latest revision as of 18:08, 30 October 2024
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 instructions
Please enter the following code, presented in the boxes below, directly in your shell/command line on bwUniCluster2.0.
Preparations
Installing glmnet involves compiling source code. Therefore, ensure that the following flags are set in $HOME/.R/Makevars:
cat ~/.R/Makevars CXX14=g++ CXX17=g++ CXX14FLAGS += -std=c++14 CXX17FLAGS += -std=c++17 CXXFLAGS = -O3 -fPIC -march=cascadelake -ffp-contract=off -fno-fast-math -fno-signed-zeros -fopenmp -Wno-unknown-warning-option
If necessary, the appropriate compiler flags can be set by running the following lines of code:
mkdir -p ~/.R echo "CXX14=g++" > ~/.R/Makevars echo "CXX17=g++" >> ~/.R/Makevars echo "CXXFLAGS = -O3 -fPIC -march=cascadelake -ffp-contract=off -fno-fast-math -fno-signed-zeros -fopenmp -Wno-unknown-warning-option" >> ~/.R/Makevars echo "CXX14FLAGS += -std=c++14" >> ~/.R/Makevars echo "CXX17FLAGS += -std=c++17" >> ~/.R/Makevars
Since installing glmnet involves compiling, we start an interactive session on one of the compute nodes:
salloc -n 1 -t 30 -p dev_single
Within the interactive session, load the R 4.4.1 module and provide configuration information to install the R package v8, rstan depends on.
# Load the R software module: module load math/R/4.4.1-mkl-2022.2.1-gnu-13.3 # Provide configuration information for the v8 R package export DOWNLOAD_STATIC_LIBV8=1
Installing the R package(s) [takes roughly 20 min]
Now, start R and install RStan using the lines of code below:
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)