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SeisSol is a software package for simulating wave propagation and dynamic rupture based on the arbitrary high-order accurate derivative discontinuous Galerkin method (ADER-DG).
Website: https://seissol.org/
Documentation: https://seissol.readthedocs.io/en/latest/
Build
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Building SeisSol
The list of necessary dependencies to install and compile can be found under https://seissol.readthedocs.io/en/latest/compiling-seissol.html (TODO: The installation in the home directory, as described in there, is outdated). In particular, you will need to install:
Python
MPI
Hdf5
Netcdf
yaml-cpp
easi https://github.com/SeisSol/easi
Lua
Eigen
ParMETIS
libxsmm
For GPUs, you will also need:
AdaptiveCpp
gemmforge https://github.com/SeisSol/gemmforge
chainforge https://github.com/SeisSol/chainforge
Alternatively, we provide a Spack environment under https://github.com/SeisSol/seissol-spack-aid .
For SeisSol itself, you will need to set the architecture you are going to use—since our matrix kernel generators usually require that information. That can be done via the HOST_ARCH
parameter. On x86 architectures without AVX512 support, choose either hsw
, rome
, or milan
as host architecture. With AVX512 support, choose skx
or bergamo
. On ARM machines, we have the dummy targets neon
, sve128
, sve256
, and sve512
, respectively. Setting these will enable the instruction generation for the respective SIMD architecture instructions. You should also set your CPU by the -mcpu
parameter.
For GPUs, you will also need to set the DEVICE_ARCH
and DEVICE_BACKEND
parameters.
Testing Your Installation
Once the build is finished, you will obtain two binaries:
SeisSol_Release_ARCH
SeisSol_proxy_Release_ARCH
To test your installation, you can do so within two steps:
Run
SeisSol_proxy_Release_ARCH 100000 100 all
. This command will give you an idealized performance figure, and also run through all kernels once.Run
SeisSol_Release_ARCH
with a parameter file. We provide reference values for all scenarios in the https://github.com/SeisSol/precomputed-seissol repository which you could use to test your installation.
Pinning and Performance Considerations
For optimal performance, we recommend using one process per NUMA domain. If you use the GPU version, you will need one process per GPU.
Furthermore, we recommend keeping one CPU core per process free, to be used for the so-called communication thread. It will be used for advancing MPI communication and IO instead. To do so, you will need to set some environment variables, similar to the following snippet:
Code Block |
---|
THREADS_PER_TASK=16 # TODO: set
CPU_HYPERTHREADING=2 #TODO: set
NUM_CORES=$(expr $CPUS_PER_TASK / $CPU_HYPERTHREADING)
NUM_COMPUTE_CORES=$(expr $NUM_CORES - 1)
export OMP_NUM_THREADS="$(expr $NUM_COMPUTE_CORES \* $CPU_HYPERTHREADING)"
export OMP_PLACES="cores($NUM_COMPUTE_CORES)"
export PROC_BIND=spread
export MP_SINGLE_THREAD=no
unset KMP_AFFINITY |
Alternatively, you can also disable the communication thread, by setting SEISSOL_COMMTHREAD=0
.
Tasks and Submissions
Run the application on 4 CPU nodes and submit the results
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