ecWAM

---

The ECMWF wave model ecWAM

Introduction

The ECMWF Ocean Wave Model (ecWAM) describes the development and evolution of wind generated surface waves and their height, direction and period. ecWAM is solely concerned with ocean wave forecasting and does not model the ocean itself: dynamical modelling of the ocean can be done by an ocean model such as NEMO.

• ecWAM may be used as a standalone tool that can produce a wave forecast driven by external forcings provided via GRIB files.
• Alternatively it can be used in a coupled mode where it provides feedback and receives forcings from
  • the atmospheric forecast model IFS.
  • the dynamic ocean model NEMO.

For more information, please go to https://confluence.ecmwf.int/display/FUG/2.2+Ocean+Wave+Model+-+ECWAM

License

ecWAM is distributed under the Apache License Version 2.0. See LICENSE file for details.

Installing ecWAM

Supported Platforms

• Linux
• Apple MacOS

Other UNIX-like operating systems may work too out of the box.

Requirements

• Fortran and C compiler, and optionally C++ compiler
• CMake (see https://cmake.org)
• ecbuild (see https://github.com/ecmwf/ecbuild)
• fiat (see https://github.com/ecmwf-ifs/fiat)
• eccodes (see https://github.com/ecmwf/eccodes)
• field_api (see https://github.com/ecmwf-ifs/field_api)
• Python with pyyaml + fypp or fckit (see https://github.com/ecmwf/fckit)

Further optional dependencies:

• MPI Fortran libraries
• multio (see https://github.com/ecmwf/multio)
• ocean model (e.g. NEMO or FESOM)
• loki (see https://github.com/ecmwf-ifs/loki)

Some driver scripts to run tests and validate results rely on availability of:

• md5sum (part of GNU Coreutils; on MacOS, install with brew install coreutils)
• Python with pyyaml or fckit

Building ecWAM

Environment variables

$ export ecbuild_ROOT=<path-to-ecbuild>
$ export MPI_HOME=<path-to-MPI>
$ export fiat_ROOT=<path-to-fiat>
$ export eccodes_ROOT=<path-to-eccodes>
$ export field_api_ROOT=<path-to-field_api>
$ export fckit_ROOT=<path-to-fckit> (optional)
$ export CC=<path-to-C-compiler>
$ export FC=<path-to-Fortran-compiler>
$ export CXX=<path-to-C++-compiler>

If you want to pre-download or install extra data files, run in the source-directory before CMake (re)configuration:

$ share/ecwam/data/populate.sh

You must compile ecWAM out-of-source, so create a build-directory

$ mkdir build && cd build

Configuration of the build happens through standard CMake

$ cmake <path-to-source>

Extra options can be added to the cmake command to control the build:

• -DCMAKE_BUILD_TYPE=<Debug|RelWithDebInfo|Release|Bit> default=RelWithDebInfo (typically -O2 -g)
• -DENABLE_TESTS=<ON|OFF>
• -DENABLE_MPI=<ON|OFF>
• -DENABLE_OMP=<ON|OFF>
• -DCMAKE_INSTALL_PREFIX=<install-prefix>

More options to control compilation flags, only when defaults are not sufficient

• -DOpenMP_Fortran_FLAGS=<flags>
• -DCMAKE_Fortran_FLAGS=<fortran-flags>
• -DCMAKE_C_FLAGS=<c-flags>

Once this has finished successfully, run make and make install.

An informational tool ecwam [--help] [--info] [--version] [--git] is available upon compilation and can be used the to verify compilation options and version information of ecWAM.

Optionally, tests can be run to check succesful compilation, when the feature TESTS is enabled (-DENABLE_TESTS=ON, default ON)

$ ctest

Generate derived-types data structures

The derived-types storing grid-point data in ecWam can be configured in src/ecwam/yowfield_mod_config.yaml, which is used to expand the accompanying src/ecwam/yowfield_mod.fypp into Fortran derived-type objects. The glue-code required to turn the derived-types members into FIELD API objects is also generated.

Build using ecWAM bundle

Another way of building ecWAM is to use the bundle definition included in package/bundle:

$ ./package/bundle/ecwam-bundle create  --bundle package/bundle/bundle.yml # Checks out dependency packages
$ ./package/bundle/ecwam-bundle build [--build-type=<build-type>] [--arch=<path-to-arch>] [--option]

The bundle also facilitates setting environment variables and compiler flags relevant to certain architectures by specifying the corresponding arch file at the build step. For example, to build on the ECMWF Atos system using Intel compilers and the hpcx-openmpi MPI library:

--arch=package/bundle/arch/ecmwf/hpc2020/intel/2021.4.0/hpcx-openmpi/2.9.0

The following options can also be configured during the bundle build step:

• --without-mpi - Disable MPI
• --without-omp - Disable OpenMP
• --single-precision - Build single-precision variant of ecWAM

Finally, additional CMake options can also be set during the bundle build step:

--cmake-"OPTION=<arg>"

Running ecWAM

Following are instructions to run ecWAM as a standalone wave forecasting tool.

A YAML configuration file is required. See tests directory for examples.

To run, use the commands listed in following steps, located in the build or install bin directory. Each of following commands can be inquired with the --help argument. If --run-dir argument is not specified, or ECWAM_RUN_DIR environment variable is not set, then the current directory is used. If --config argument is not specified, it is assumed that a file called config.yml is present in the <run-dir>.

1. Create bathymetry and grid tables

ecwam-run-preproc --run-dir=<run-dir> --config=<path-to-config.yml>

This command generates bathymetry data files as specified by configuration options. As bathymetry data files are large and require heavy computations they are cached for later use in a directory which can be chosen with the --cache argument, or ECWAM_CACHE_PATH environment variable. By default the cache path will be $HOME/cache/ecwam unless on the ECMWF HPC it is in $HPCPERM/cache/ecwam. Bathymetry data files can also be searched for in a hierarchy of cache-like directories specified with the ECWAM_DATA_PATH variable containing a ':'-separated list of paths (like $PATH). If not found, they are attempted to be downloaded from URL https://get.ecmwf.int/repository/ecwam. If still not available, they will be computed. The cache path will then be populated with computed, or downloaded data, or with symbolic links to found data in the ECWAM_DATA_PATHs.

Grid tables are always computed and never cached. THey are placed in the <run-dir>

2. Create initial conditions

ecwam-run-preset --run-dir=<run-dir> --config=<path-to-config.yml>

As a result files, binary files of the form <run-dir>/restart/BLS* and <run-dir>/restart/LAW* are created. They contain all initial conditions required for the wave model run from "cold start". This command requires surface wind and sea-ice-cover input, at initial simulation time, provided in GRIB format. The configuration file must specify this file. For several benchmark or test cases, they are retrieved in similar fashion as the bathymetry files (see above).

This package also contains some scripts to generate MARS requests to retrieve data from the ECWMF operational forecast or from the ERA5 reanalysis data set. This is useful to generate new tests or for longer runs.

3. Run wave model

ecwam-run-model --run-dir=<run-dir> --config=<path-to-config.yml>

With initial conditions, forcings, and grid tables in place we can run the actual wave model. The advection and physics time step needs to be configured via the configuration file in accordance the grid resolution. The configuration file offers options to output GRIB output fields at regular time intervals, or binary restart files similar to the initial condition files generated in step 2. After the run, the output files will be in <run-dir>/output/ and log files will be in <run-dir>/logs/model. One log file called statistics.log contains computed norms which can be used to validate results. Such validation will occur automatically when the configuration file contains a validation section. See tests directory for example configuration files.

Running with MPI

Above commands by default run without MPI. To use MPI, or apply a custom command prefixed to the binary execution, there are following options:

• Use argument --launch="ecwam-launch -np <NTASKS> -nt <NTHREADS>". ecwam-launch is an internal "smart" launcher that chooses a good launcher depending on availability and the used platform. It will also set export OMP_NUM_THREADS=<NTHREADS> for you. The unit-tests are automatically configured to use this when invoked via ctest.

• Use arguments -np <NTASKS> -nt <NTHREADS>. This is equivalent to the above, and internally uses the ecwam-launch launcher.

• Use any other custom command, e.g. --launch="srun -n <NTASKS> -c <NTHREADS>" for full control. Note that this does not automatically export the OMP_NUM_THREADS variable.

Note that only ecwam-run-model currently supports MPI.

GPU offload

ecWAM can be offloaded for GPU execution. GPU optimised code for the wave propagation kernel is commited to source, whereas GPU code for the source-term computation is generated at build-time build-time using ECMWF's source-to-source translation toolchain Loki. Currently, three Loki transformations are supported:

• Single-column-coalesced (scc): Fuse vector loops and promote to the outermost level to target the SIMT execution model
• scc-hoist: The scc transformation with temporary arrays hoisted to the driver-layer (the default)
• scc-stack: The scc transformation with a pool allocator used to allocate temporary arrays

The scc-hoist and scc-stack transformations offer superior performance to the scc transformation. Currently, only the OpenACC programming model on Nvidia GPUs is supported.

NB: GPU offload is not yet supported for ecWAM 1.4.x.

Building

The recommended option for building the GPU enabled ecWAM is to use the provided bundle, and pass the --with-loki --with-acc options. Different Loki transformations can also be chosen at build-time via the following bundle option: --loki-mode=<trafo>. Direct GPU-to-GPU MPI communications can be enabled by passing the --with-gpu-aware-mpi option.

The ecwam-bundle also provides appropriate arch files for the nvhpc suite on the ECMWF ATOS system.

Running

No extra run-time options are needed to run the GPU enabled ecWam. Please note that this means that if ecWam is built using the --with-loki and --with-acc bundle arguments, it will necessarily be offloaded for GPU execution. For multi-GPU runs, the number of GPUs maps to the number of MPI ranks. Thus multiple GPUs can be requested by launching with multiple MPI ranks. The mapping of MPI ranks to GPUs assumes at most 4 GPUs per host node.

Environment variables

The Loki SCC transformation uses the CUDA runtime to manage temporary arrays and needs a large NV_ACC_CUDA_HEAPSIZE, e.g. NV_ACC_CUDA_HEAPSIZE=4G.

For running with multiple OpenMP threads and grids finer than O48, OMP_STACKSIZE should be set to at least 256M.

Known issues

1. On macOS arm64 with gfortran 12.2, and Open MPI 4.1.4, and with compilation with flag -ffpe-trap=overflow, the execution of ecwam-preproc and ecwam-chief needs to be launched with mpirun -np 1, even for serial runs in order to avoid a floating point exception during during call to MPI_INIT. The flag -ffpe-trap=overflow is set e.g. for Debug build type. Floating point exceptions on arm64 manifest as a SIGILL.
2. The coarsest configuration, i.e. O48, should be run with no more than one GPU.

Reporting Bugs

Please report bugs using a GitHub issue. Support is given on a best-effort basis by package developers.

Contributing

Contributions to ecWAM are welcome. In order to do so, please open a GitHub issue where a feature request or bug can be discussed. Then create a pull request with your contribution. All contributors to the pull request need to sign the contributors license agreement (CLA).