Compilers and MPI
In order to follow this workshop, you will need access to compilers and MPI libraries. You can either use a cluster or set things up on your own laptop, and instructions for both are provided below.
(Optional, not covered in online workshops) One part of the workshop deals with profiling parallel code using ARM Forge, and access to a SNIC cluster is required for the exercises in this part. It is convenient to install a local client to interact with the profiler running on the cluster, and instructions for setting this up are given below.
On your laptop
These instructions are based on installing compilers and MPI via the conda package manager, as it provides a convenient way to install binary packages in an isolated software environment.
- The instructions focus on installation on MacOS and Linux computers, as well as Windows computers using the Windows Subsystem for Linux (WSL).
- Instructions for installing WSL on Windows can be found here
- Installing compilers and MPI natively on Windows is also possible through Cygwin and the Microsoft Distribution of MPICH, but we recommend that you instead use WSL which is available for Windows 10 and later versions.
Begin by installing Miniconda:
- Download the 64-bit installer from here for your operating system
- for MacOS and Linux, choose the bash installer
- on Windows, open a Linux-WSL terminal and type:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh. If wget is not a recognised command, type
sudo apt-get install wgetand provide the password you chose when installing WSL.
- In a terminal, run the installer with
bash Miniconda3-latest-<operating-system>-x86_64.sh(replace with correct name of installer)
- Agree to the terms of conditions, specify the installation directory (the default is usually fine), and answer “yes” to the questions “Do you wish the installer to initialize Miniconda3 by running conda init?”
You now have miniconda and conda installed. Make sure that it works by
which conda and see that it points to where you installed
miniconda (you may have to open a new terminal first).
We recommend that you create an isolated conda environment (this is good practice in software development):
conda create --name mpi-intro python=3.7
conda activate mpi-intro
If you want to use Python for the exercises, you will need to install mpi4py. mpi4py can be installed either using pip or conda, but with pip you will need to install MPI yourself first (e.g. OpenMPI or MPICH), while conda will install its own MPI libraries. If you don’t already have MPI installed on your laptop, it will be easiest to use conda:
(mpi-intro) $ conda install -c conda-forge mpi4py
Please also verify the installation. The following command should not give an error message:
(mpi-intro) $ python -c "from mpi4py import MPI"
and the following command should give a version number:
(mpi-intro) $ mpirun --version
C/C++ and Fortran
If you want to use C, C++ or Fortran for the exercises, you will need to install compilers and MPI libraries if you don’t already have them available. This can also be done using conda:
(mpi-intro) $ conda install -c conda-forge compilers
(mpi-intro) $ conda install -c conda-forge mpich
Please also verify the installation. The following commands should give version numbers:
(mpi-intro) $ mpicc --version
(mpi-intro) $ mpifort --version
(mpi-intro) $ mpirun --version
On a PDC cluster
To do the exercises at PDC, you will need:
Below you will find instructions for how to use the Tegner cluster for either Python or C/C++/Fortran MPI applications.
Python is available through the Anaconda distribution at PDC. To use mpi4py on Tegner, you need to load an Anaconda module and then switch to a specific conda environment:
module load anaconda/py37/5.0.1
source activate mpi4py
Loading the Anaconda module will also load the modules gcc/8.2.0 and openmpi/4.0-gcc-8.2, so you will be able to run Python code with:
mpirun -n 24 python example.py
C/C++ and Fortran
We suggest that you use the gcc compiler together with OpenMPI libraries:
module load gcc/8.2.0
module load openmpi/4.0-gcc-8.2
You will then be able to compile and run MPI code with:
mpicc -o example example.c
mpifort -o example example.f90
mpirun -n 12 ./example
(not in online workshops) ARM Forge
The ARM Forge tools (Performance Reports, MAP and DDT) are installed on PDC clusters. These are graphical applications, and running them over an ssh connection can become sluggish or unstable. We therefore recommend to install the ARM Forge Remote Client, which runs on your local computer and can be used to connect to running processes on the cluster.
Begin by downloading the Remote Client, and installing it. Next you need to set up the connection to PDC:
- Open up the ARM Forge Client
- Click “Remote Launch”, and select “Configure”
- Click “Add”, and for “hostname” write:
@tegner.pdc.kth.se. You can also give an optional Connection name.
- For “Remote installation directory”, enter
- Click on “Test Remote Launch” to see if the Remote Client GUI can successfully connect to Tegner.
If connecting fails, you may need to replace the default ssh used by
Remote Client. First create the directory
~/.allinea. In this
directory create a file called
remote-exec. In this file, write
#!/bin/sh /correct/path/to/ssh [correct flags] $*
- If you are on OSX with an ssh installed via MacPorts,
the correct ssh would be
- If you have not configured your
~/.ssh/configfile, you will need to add the flags
GSSAPIDelegateCredentials=yes -o GSSAPIKeyExchange=yes -o GSSAPIAuthentication=yes