ScalFMM: Fast Multipole Method

ScalFMM is a C++ library that implements a kernel independent Fast Multipole Method.

Copyright Inria, please read the licence.

Requirements

• CMake v3.18.0 or later
• C++ compiler that supports
  • C++17 compiler support list
  • OpenMP
• Custom BLAS, FFT implementations.

The following are optional:

• Doxygen to build the documentation.
• Sphinx and extensions (see the doc section) to build the documentation. In this case, we need the following packages: breathe, exhale, recommonmark and sphinx-rtd-theme.
• An MPI implementation to build the distributed files.
• StarPU for the relevant FMM implementations.

ScalFMM depends on the complete xtensor stack. The following modules are embedded as submodules : - xtl - xsimd - xtensor - xtensor-blas - xtensor-fftw

We also retrieve cpp_tools as a submodule which is a collection of small cpp helpers.

Get and Build ScalFMM

The different branches in ScalFMM

• main latest development
• master-2.0 the master of the 2.0 version (no evolution)
• maintenance (the official version )
  • scalfmm-3.0 the release of the 3.0 version
  • scalfmm-2.0 the release of the 2.0 version (no evolution)
  • scalfmm-1.5 the release of the 1.5 version (no evolution)

Features

• scalfmm-3.0 the release of the 3.0 version
  • barycentric, Chebyshev, uniform interpolation
  • uniform tree
  • task based OpenMP,MPI
• scalfmm-2.0 the release of the 2.0 version
  • adaptive and uniform tree
  • Chebyshev, uniform interpolation
  • MPI, OpenMP, StarPU (Chebyshev P2P and M2L operators for GPU)
• scalfmm-1.5 the release of the 1.5 version
  • uniform tree
  • Chebyshev, uniform interpolation
  • MPI, OpenMP, StarPU (Chebyshev P2P and M2L operators for GPU)

Cloning

To use the last development states of ScalFMM, please clone the main branch. Note that ScalFMM contains multiple git submodules like morse_cmake and the xtensor software stack. To get sources please use these commands:

git clone --recursive https://gitlab.inria.fr/solverstack/ScalFMM.git

or

git clone https://gitlab.inria.fr/solverstack/ScalFMM.git
cd ScalFMM
git submodule init
git submodule update

Building

The project has been tested with the following compiler both on Linux and OSX

• GCC 11 and above
• LLVM 17 and above

ScalFMM uses iterators on task dependencies (OpenMP 5.x) the following compilers do not support them yet

• Intel OneAPI 2022 and lower

To keep a clean source tree, do an out-of-source build by creating a build folder out of your clone.

OpenMP or sequential installation

On Linux

cd /path/to/build/
# Use cmake, with relevant options
cmake .. # -Dscalfmm_USE_MKL=ON 

The build may be configured after the first CMake invocation using, for instance, ccmake or cmake-gui.

# Still in the build folder
ccmake .
# or
cmake-gui .

On macosX

To use Clang's native compiler, you must first install the omp library and use the -Xclang -fopenmp compilation flags.

brew install libomp

and to compile

cd /path/to/build/
# Use cmake, with relevant options
cmake  -DCMAKE_CXX_FLAGS= `-Xclang -fopenmp`  -S ../ 

Optimization

Customization or optimized options:

• If you plan to use Intel MKL, please set scalfmm_USE_MKL to ON. This will also choose MKL for the FFTs and prevent unusual behavior with multithreaded MKL version.
• To use a specific version of labpack/blas you can specify it using the BLA_VENDOR variable in cmake. For example -DBLA_VENDOR=OpenBLAS for OpenBLAS lapack and blas library
• if we are interested in periodic boundary condition, the option scalfmm_BUILD_PBC has to be set to ON.

The binaries are then compiled by calling make (or ninja if you specified it at the configure step).

The all target only build the tools binaries. These are binaries that can generate particle distributions, perform direct fmm computation, etc.

Invoke make help to see the available targets. Global targets are available :

• examples builds the examples in the examples folder,
• units builds the unit tests in the units folder.

If you want the examples, run make examples.

You can also specify your install directory with -DCMAKE_INSTALL_PREFIX=/path/to/your/install and then call make install

MPI installation

On macosX

Be careful if you install openMPI with brew, you must compile with the gcc version of brew. To do construct openmpi with gcc@12, we run the following command

brew install open-mpi  --cc=gcc-12

and make be sure that mpicc, mpic++ and mpiexec are in your path.

Then to construct ScalFMM with MPI do

 CC=/usr/local/Cellar/open-mpi/4.1.5/bin/mpicc \
 CXX=/usr/local/Cellar/open-mpi/4.1.5/bin/mpic++ \
 cmake -DCMAKE_CXX_FLAGS="-march=native" -Dscalfmm_USE_MKL=ON  -Dscalfmm_USE_MPI=ON  -S ../ -B.

Performance

When building ScalFMM, remember that performance depends on SIMD support. If you are targeting a specific architecture, add the appropriate SIMD flag to your version flags. For example, if you are targeting an AVX2 processor, add -mavx2 to your flags. And if you know the microarchitecture, such as cascade lake for example, you can also add the -march=cascadelake flag. When you add architecture flags, SIMD flags are automatically triggered.

Using ScalFMM in your project

To find ScalFMM, pkgconfig can be used within your CMake and all ScalFMM dependencies will be found automatically. Here is an example :

find_package(scalfmm CONFIG REQUIRED)
if(scalfmm_FOUND)
  message(STATUS "ScalFMM Found")
  add_executable(my_exe program.cpp )
  target_link_libraries(my_exe scalfmm::scalfmm)
else()
  message(FATAL_ERROR "ScalFMM NOT FOUND")
endif()

pkgconfig will find the following targets:

• scalfmm::scalfmm with sequential and OpenMP support.
• scalfmm::scalfmm-headers with only the headers, requires full configuration and linking with dependencies on your side.
• scalfmm::scalfmm-mpi and scalfmm::scalfmm-starpu (UNDER DEVELOPMENT) with distributed support.

Building the Doc

The doc can be found here or you can build it locally.

You will need the following to build the doc :

- Doxygen : install has you wish, through your package manager for example.
- Sphinx : `pip install -U Sphinx`
- Breathe : `pip install breathe`
- Exhale : `pip install exhale`
- Recommonmark : `pip install recommonmark`
- Sphinx Read The Doc Theme : `pip install sphinx_rtd_theme`

cd path/to/build
cmake .. -Dscalfmm_BUILD_DOC=ON # or if cmake has already been called, ccmake .
make doc

This will generate the documentation in HTML format in the build/docs/sphinx folder.

# From the Build folder
cd docs/sphinx
firefox index.html

A quick start file (QUICKSTART.md) is available, as well as user documentation. The latter is in orgmode, to generate the html you have to generate it by

emacs docs/user_guide.org  --batch -f org-html-export-to-html --kill

of for pdf file

emacs docs/user_guide.org  --batch -f org-latex-export-to-pdf --kill

Contributing and development guidelines

Gitlab flow

Please, read the Gitlab flow article available here.

To make it simple, if you want to contribute to the library, create a branch from experimental with a meaningful name and develop your feature in that branch. Keep your branch up to date by regularly rebasing your branch from the experimental branch to be up to date. Once you are done, send a merge request.

Branches

• maintenance/scalfmm-1.5 and maintenance/scalfmm-2.0 are main maintenance branches for older ScalFMM versions.
• experimental is the main branch for ScalFMM 3.0.

If you wish to contribute or test new features, please branch from experimental.

Folder structure

• include: library core.
• check: tools to check scalfmm functionalities.
• data: particle distribution examples.
• examples: common usage examples.
• doc: documentation configuration.
• units: unit tests.
• tools: binaries to handle data files.
• modules: dependencies required.