Iceberg was decommissioned on 30th November 2020. Users of Iceberg need to switch to using ShARC and/or Bessemer instead.
R is a statistical computing language. This version of R is built using the Intel compilers and the Intel Math Kernel Library. This combination can result in significantly faster runtimes in certain circumstances.
Most R extensions are written and tested for the gcc suite of compilers so it is recommended that you perform testing before switching to this version of R.
The Intel build of R makes use of CPU instructions that are only present on the most modern of Iceberg’s nodes. In order to use them, you should add the following to your batch submission scripts:
#$ -l arch=intel-e5-2650v2
If you do not do this, you will receive the following error message when you try to run R:
Please verify that both the operating system and the processor support Intel(R) F16C and AVX instructions.
After connecting to iceberg (see Establishing a SSH connection), start an interactive session with the
There are two types of the Intel builds of R,
parallel`.` ``sequential makes use of one CPU core and can be used as a drop-in replacement for the standard version of R installed on Iceberg.
module load apps/intel/15/R/3.3.1_sequential
parallel version makes use of multiple CPU cores for certain linear algebra routines since it is linked to the parallel version of the Intel MKL. Note that only linear algebra routines are automatically parallelised.
module load apps/intel/15/R/3.3.1_parallel
When using the parallel module, you must also ensure that you set the bash environment variable
OMP_NUM_THREADS to the number of cores you require and also use the openmp parallel environment. E.g. Add the following to your submission script:
#$ -pe openmp 8 export OMP_NUM_THREADS=8 module load apps/intel/15/R/3.3.1_parallel
Here is how to run the R script called
linear_algebra_bench.r from the HPC Examples github repository:
#!/bin/bash #This script runs the linear algebra benchmark multiple times using the intel-compiled version of R #that's linked with the sequential MKL #$ -l rmem=8G # Target the Ivy Bridge Processors #$ -l arch=intel-e5-2650v2 module load apps/intel/15/R/3.3.1_sequential echo "Intel R with sequential MKL on intel-e5-2650v2" Rscript linear_algebra_bench.r output_data.rds
Here is how to run the same code using 8 cores:
#!/bin/bash #$ -l rmem=3G # Memory per core # Target the Ivy Bridge Processors #$ -l arch=intel-e5-2650v2 #$ -pe openmp 8 export OMP_NUM_THREADS=8 module load apps/intel/15/R/3.3.1_parallel echo "Intel R with parallel MKL on intel-e5-2650v2" echo "8 cores" Rscript inear_algebra_bench.r 8core_output_data.rds
By default, the standard version of R allows you to install packages into the location
~ refers to your home directory.
To ensure that the Intel builds do not contaminate the standard gcc builds, the Intel R module files set the environment variable
R_LIBS_USER to point to
As a user, you should not need to worry about this detail and just install packages as you usuall would from within R. e.g.
The Intel build of R will ignore any packages installed in your home directory for the standard version of R and vice versa
These notes are primarily for administrators of the system.
This was a scripted install. It was compiled from source with Intel Compiler 15.0.3 and with
--enable-R-shlib enabled. It was run in batch mode.