Install

Installing Smilei requires several steps:

  1. Install compilers and libraries that Smilei needs (dependencies)

  2. Download Smilei

  3. Setup your environment (environment variables)

  4. Compile

Install the dependencies

The necessary dependencies are:

  • A C++11 compiler, optionally implementing openMP version > 4.5.

  • An MPI library (by default a version supporting MPI_THREAD_MULTIPLE). IntelMPI or OpenMPI are recommended.

  • The parallel HDF5 library compiled with your versions of C++ and MPI.

  • Python 3+ with header files.

When compiling on GPU:

  • The C++ compiler must be GPU-aware (typically nvc++ for NVIDIA or clang for AMD)

  • A CUDA or HIP compiler is necessary (typically nvcc for NVIDIA or hipcc for AMD)

Optional dependencies are:

  • Git for version control

  • Python modules for post-processing: sphinx, h5py, numpy, matplotlib, pint

  • FFmpeg for converting animations to videos

There are various ways to install all dependencies, depending on the platform:

If you have successfully installed these dependencies on other platforms, please contact us and share!

Download the Smilei source

Clone the latest Smilei version from Github:

cd /path/of/your/choice/
git clone https://github.com/SmileiPIC/Smilei.git

If you prefer a direct download, see here.

Setup environment variables for compilation

Several environment variables may be required, depending on your setup.

  • SMILEICXX: the MPI-C++ compiler. Defaults to mpicxx.

  • HDF5_ROOT_DIR: the folder of the HDF5 library. Defaults to $HDF5_ROOT.

  • BUILD_DIR: the folder where the compilation should occur. Defaults to ./build.

  • PYTHONEXE: the python executable to use in smilei. Defaults to python.

  • CXXFLAGS: flags for the C++ compiler.

  • LDFLAGS: flags for the linker.

  • GPU_COMPILER: the compiler for CUDA or HIP (typically nvcc or hipcc). Defaults to $CC.

  • GPU_COMPILER_FLAGS: flags for $GPU_COMPILER.

The command make help can give you some information about your environment.

Compile Smilei

In a terminal, go to the folder where you downloaded Smilei and use the commmand

make

If the compilation is successful, you should now have a new smilei executable.

Advanced compilation options

Compile with several processors (fast compilation)

make -j 4  # Compiles on 4 threads

Compilation configuration with keyword “config”

make config=noopenmp        # Without OpenMP support
make config=no_mpi_tm       # Without a MPI library which supports MPI_THREAD_MULTIPLE
make config=gpu_nvidia      # For Nvidia GPU acceleration
make config=gpu_amd         # For AMD GPU acceleration
make config=debug           # With debugging output (slow execution)
make config=scalasca        # For the Scalasca profiler
make config=advisor         # For Intel Advisor
make config=vtune           # For Intel Vtune
make config=inspector       # For Intel Inspector
make config=detailed_timers # More detailed timers, but somewhat slower execution

It is possible to combine arguments above within quotes, for instance:

make config="debug noopenmp" # With debugging output, without OpenMP

Obtain some information about the compilation

make print-XXX               # Prints the value of makefile variable XXX
make env                     # Prints the values of all makefile variables
make help                    # Gets some help on compilation

Machine-specific compilation

Each machine may require a specific configuration (environment variables, modules, etc.). These instructions may be included in a file of your choice, via the machine argument:

make machine=my_machine_file

where my_machine_file is a file, located in scripts/compile_tools/machine, containing the lines of command to be executed before compilation. If you successfully write such a file for a common supercomputer, please share it with developpers so that it can be included in the next release of Smilei.

Compilation for GPU accelerated nodes

On GPU, two compilers are used:

  • for .cpp files, a GPU-aware C++ compiler defined by the variable $SMILEICXX,

  • and for .cu files, a CUDA compiler defined by the variable $GPU_COMPILER.

For nVidia GPUs, it is recommended to use the nvhpc software kit which includes the compilers nvc++ and nvcc. For AMD GPUs, the equivalent ROCm software kit includes clang and hipcc.

Generally, several flags must be supplied to these compilers in order to target properly your system architecture. They must be supplied in $CXXFLAGS and $GPU_COMPILER_FLAGS, respectively. Please refer to the system administrators to find available compilers and the required flags for your machine, as well as the commands needed to load the correct environment.

The compilation of Smilei must include a special config keyword equal to either gpu_nvidia or gpu_amd. Two examples are provided as guidance:

make -j 12 machine="jean_zay_gpu_A100" config="gpu_nvidia" # example for Nvidia GPU
make -j 12 machine="adastra" config="gpu_amd"              # example for AMD GPU

In these cases, the environment variables were included in machine files that you can find in the folder scripts/compile_tools/machine/. Typically CXXFLAGS += -ta=tesla:cc80 for nvhpc <23.4 and CXXFLAGS += -gpu=cc80 -acc for the more recent versions of nvhpc.

Warning

The biggest challenge to execute Smilei on an accelerator is the correct installation of the MPI and HDF5 libraries. They must be compiled with the GPU-aware c++ compiler after configuring (ie. ./configure --options) with the appropriate options specific to your system.

For testing purposes, Smilei can be run on a linux PC with a good GPU. As a guidance, read these instructions for GPU on linux.

Optimization and vectorization options explained

To tune optimization and vectorization options, Smilei uses the machine files described above. They contain compiler options for specific hardware architectures or processor families.

This page explains in detail optimization flags used in machine files and therefore how to generate your own machine file.

Create the documentation

If you have installed the python module sphinx, you can create the documentation (which you are currently reading) with:

make doc

This creates a local html website accessible in your build/html/ folder.

Install the happi module

A python module, happi, is provided to view, extract and post-process data from all the diagnostics. There are several ways to load this module in python.

  1. Recommended:

make happi

This has to be done only once, unless you move the smilei directory elsewhere. This command creates a small file in the Python user-site directory that tells python where to find the module. To remove it use the command make uninstall_happi.

The module will directly be accessible from python:

>>> import happi

  1. Alternative: Execute the Diagnostics.py script from python

Adding a new python module is not always possible. Instead, we provide the script Diagnostics.py which is able to find the happi module and import it into python.

You may add the following command in your own python script:

>>> execfile("/path/to/Smilei/scripts/Diagnostics.py")

Install the smilei_tables tool

Generation of the tables is handled by an external tools. A full documentation is available on the dedicated page.