PSyclone is a source-to-source Fortran compiler designed to programmatically optimise, parallelise and instrument HPC applications via user-provided transformation scripts. By encapsulating the performance-portability aspects (e.g. whether to parallelise with OpenMP or OpenACC), these scripts enable a separation of concerns between the scientific implementation and the optimisation choices. This allows each aspect to be explored and developed largely independently. Additionally, PSyclone supports the development of kernel-based Fortran-embedded DSLs following the PSyKAl model developed in the GungHo project.
PSyclone is currently used to support the LFRic mixed finite-element PSyKAl DSL for the UK MetOffice's next generation modelling system and the GOcean finite-difference PSyKAl DSL for a prototype 2D ocean modelling system. It is also used to insert GPU offloading directives into existing directly-addressed MPI applications such as the NEMO ocean model.
For more detailed information see the PSyclone Documentation.
You can install the latest release of psyclone from PyPI by using:
$ pip install psyclone
or, if you want an isolated installation in a python virtual environment:
$ python -m venv <virtual_env_name>
$ source <virtual_env_name>/bin/activate
$ pip install psyclone
Alternatively, you can install the latest upstream version of psyclone by cloning this repository and using:
$ pip install .
or in developer (editable) mode using
$ pip install -e .
PSyclone is also available in the Conda and Spack package managers.
For more information about the installation process see the Getting Going. section of the User Guide.
| Path | Description |
|---|---|
| bin/ | Top-level driver scripts for PSyclone and the PSyclone kernel tool |
| changelog | Information on changes between releases |
| doc/ | Documentation source using Sphinx |
| examples/ | Simple examples |
| README.md | This file |
| src/psyclone | The Python source code |
| src/psyclone/tests/ | Unit and functional tests using pytest |
| tutorial/practicals | Hands-on exercises using a local installation of PSyclone |