SPH

The smoothed particle hydrodynamics (SPH) technique is a purely Lagrangian method. SPH discretizes a fluid in a series of interpolation points (SPH particles) whose distribution follows the mass density of the fluid and their evolution relies on a weighted interpolation over close neighboring particles.

SPH simulations represent computationally demanding calculations. Therefore, trade-offs are made between temporal and spatial scales, resolution, dimensionality (3-D or 2-D), and approximated versions of the physics involved. The parallelization of SPH codes is not trivial due to their boundless nature and the absence of a structured grid. SPHYNX, ChaNGa, and SPH-flow are the three SPH codes selected in the PASC SPH-EXA project to act as parent and reference codes to SPH-EXA. The performance of these three codes is negatively impacted by factors such as imbalanced multi-scale physics, individual time-stepping, halos exchange, and long-range forces. Therefore, the goal is to extrapolate their common basic SPH features, and consolidate them in a fully optimized, Exascale-ready, MPI+X, SPH code: SPH-EXA.

SPH-EXA

SPH-EXA is a C++20 simulation code for hydrodynamics simulations (with gravity and other physics), parallelized with MPI, OpenMP, CUDA, and HIP.

Check our wiki for more details

Folder structure

SPH-EXA
├── README.md
├── docs
├── domain                           - Cornerstone library: octree building and domain decomposition
│   ├── include
│   │   └── cstone
│   │       ├── CMakeLists.txt
│   │       ├── cuda
│   │       ├── domain
│   │       ├── findneighbors.hpp
│   │       ├── halos
│   │       ├── primitives
│   │       ├── sfc
│   │       ├── tree
│   │       └── util
│   └── test                        - Cornerstone unit- performance-
│       ├── integration_mpi           and integration tests
│       ├── performance
│       ├── unit
│       └── unit_cuda
├── ryoanji                         - Ryoanji: N-body solver for gravity
│   ├─── src
│   └─── test                       - demonstrator app and unit tests
│
├── sph                             - SPH implementation
│   ├─── include
│   │    └── sph
│   └─── test                       - SPH kernel unit tests
│
└── src
    ├── init                        - initial conditions for test cases
    ├── io                          - file output functionality
    └── sphexa                      - SPH main application front-end

Toolchain requirements

The C++ (.cpp) part of the code requires a C++20 compiler, at least GCC 10, clang 12 or cray-clang 14. For CUDA (.cu), the minimum supported CUDA version is CUDA 11.2 with a C++17 host compiler, e.g. GCC 9.3.0.

Note that GCC 10.3.0 does not work as CUDA host compiler due to known compiler bugs. For ease of use, the recommended minimum version of CUDA is 11.4.1 which supports GCC 11, providing both the required C++20 support and bug-free CUDA host compilation. [NOTE: CUDA/11.3.1 seems to have solved the compatibility issues with GCC 10.3.0]

Compilation

Minimal CMake configuration:

mkdir build
cd build
cmake <GIT_SOURCE_DIR>

Compilation at sciCORE (UniBas):

ml HDF5/1.10.7-gompi-2021a
ml CMake/3.23.1-GCCcore-10.3.0
ml CUDA/11.3.1

mkdir build
cd build
cmake <GIT_SOURCE_DIR>

CMake configuration on Piz Daint for clang: Cray-clang 14 for CPU code (.cpp), CUDA 11.6 + GCC 11.2.0 for GPU code (.cu):

module load daint-gpu
module load CMake/3.22.1
module load PrgEnv-cray
module load cdt/22.05           # will load cce/14.0.0
module load nvhpc-nompi/22.2    # will load nvcc/11.6
module load gcc/11.2.0
module load cray-hdf5-parallel

mkdir build
cd build

# C-compiler is needed for hdf5 detection
CC=cc CXX=CC cmake -DCMAKE_CUDA_ARCHITECTURES=60 -S <GIT_SOURCE_DIR>

Build everything: make -j

Running the main application

The main sphexa application can either start a simulation by reading initial conditions from a file or generate an initial configuration for a named test case. Self-gravity will be activated automatically based on named test-case choice or if the HDF5 initial configuration file has an HDF5 attribute with a non-zero value for the gravitational constant.

Arguments:

• --init CASE/FILE : sedov for simulation the Sedov blast wave, noh for the Noh implosion, evrard for the Evrard collapse or provide an HDF5 file with valid input data
• -n NUM : Run the simulation with NUM^3 (NUM to the cube) number of particles (for named test cases)
• -s NUM : Run the simulation with NUM of iterations (time-steps)
• -w NUM : Dump particle data every NUM iterations (time-steps)
• -f FIELDS: Comma separated list of particle fields for file output dumps
• --quiet : Don't print any output to stdout

Example usage:

• OMP_NUM_THREADS=4 ./sphexa --init sedov -n 100 -s 1000 -w 10 -f x,y,z,rho,p Runs Sedov with 100^3 particles for 1000 iterations (time-steps) with 4 OpenMP threads and dumps particle xyz-coordinates, density and pressure data every 10 iterations
• OMP_NUM_THREADS=4 ./sphexa-cuda --init -n 100 -s 1000 -w 10 -f x,y,z,rho,p Runs Sedov with 100^3 million particles for 1000 iterations (time-steps) with 4 OpenMP threads. Uses the GPU for most of the compute work.
• OMP_NUM_THREADS=4 mpiexec -np 2 ./sphexa --init noh -n 100 -s 1000 -w 10 Runs Noh with 100^3 million particles for 1000 iterations (time-steps) with 2 MPI ranks of 4 OpenMP threads each. Works when using MPICH. For OpenMPI, use mpirun instead.
• OMP_NUM_THREADS=12 srun -Cgpu -A<your account> -n<nnodes> -c12 ./sphexa-cuda --init sedov -n 100 -s 1000 -w 10 Optimal runtime configuration on Piz Daint for nnodes GPU compute nodes. Launches 1 MPI rank with 12 OpenMP threads per node.
• ./sphexa-cuda --init evrard.h5 -s 2000 -w 100 -f x,y,z,rho,p,vx,vy,vz Run SPH-EXA, initializing particle data from an input file (e.g. for the Evrard collapse). Includes gravitational forces between particles. The angle dependent accuracy parameter theta can be specificed with --theta <value>, the default is 0.5.

Running the unit, integration and regression tests

Cornerstone octree and domain unit tests:

./domain/test/unit/component_units

GPU-enabled unit tests:

./domain/test/unit_cuda/component_units_cuda

MPI-enabled integration and regression tests:

mpiexec -np 2 ./domain/test/integration_mpi/domain_2ranks
mpiexec -np 2 ./domain/test/integration_mpi/exchange_focus
mpiexec -np 2 ./domain/test/integration_mpi/exchange_halos
mpiexec -np 2 ./domain/test/integration_mpi/globaloctree

mpiexec -np 5 ./domain/test/integration_mpi/domain_nranks
mpiexec -np 5 ./domain/test/integration_mpi/exchange_domain
mpiexec -np 5 ./domain/test/integration_mpi/exchange_keys
mpiexec -np 5 ./domain/test/integration_mpi/focus_tree
mpiexec -np 5 ./domain/test/integration_mpi/treedomain

SPH-kernel unit tests:

./include/sph/test/kernel/kernel_tests

Input data

Some tests require input data. For example, the Evrard test case will check that a Test3DEvrardRel.bin file exists and can be read at the beginning of the job. This file can be downloaded from zenodo.org.

Ryoanji GPU N-body solver

Ryoanji is a high-performance GPU N-body solver for gravity. It relies on the cornerstone octree framework for tree construction, EXAFMM multipole kernels, and a warp-aware tree-traversal inspired by the Bonsai GPU tree-code.

Running the demonstrator app

./test/ryoanji <log2(numParticles)> <computeDirectReference:yes=1,no=0>

Running the unit tests

./test/ryoanji_unit_tests

Authors (in alphabetical order)

• Ruben Cabezon
• Aurelien Cavelan
• Florina Ciorba
• Jean M. Favre
• Michal Grabarczyk
• Danilo Guerrera
• David Imbert
• Sebastian Keller
• Lucio Mayer
• Ali Mohammed
• Jg Piccinali
• Tom Quinn
• Darren Reed

Paper references

Cavelan, A., Cabezon, R. M., Grabarczyk, M., Ciorba, F. M. (2020). A Smoothed Particle Hydrodynamics Mini-App for Exascale. Proceedings of the Platform for Advanced Scientific Computing Conference (PASC '20). Association for Computing Machinery. DOI: 10.1145/3394277.3401855

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

• Platform for Advanced Scientific Computing (PASC)
  • SPH-EXA project 1 and webpage
  • SPH-EXA project 2 and webpage
• Swiss National Supercomputing Center (CSCS)
• Scientific Computing Center of the University of Basel (sciCORE)
• Swiss participation in Square Kilometer Array (SKA)