JAX-ALFA: JAX-powered Atmospheric LES For All ============================================= .. image:: _static/homepage.png :width: 400px :align: center Overview -------- JAX-ALFA is a JAX-based large-eddy simulation framework for atmospheric boundary layer simulations. It leverages JAX's CPU/GPU/TPU acceleration capabilities to provide highly efficient cross-platform simulations without any code changes. Features -------- - Incompressible flow solver - Spectral methods for horizontal derivatives - Finite difference methods for vertical derivatives - FFT-based direct Poisson solver - Dynamic SGS coefficient computation - Prognostic potential temperature and specific humidity scalars - Virtual potential temperature buoyancy coupling - JAX-accelerated computations for CPUs & GPUs - Either single or double precision computations Download -------- The JAX-ALFA package can be downloaded from: https://github.com/Sukantabasu/jax-alfa Requirements ------------ - Python 3.8+ - JAX - NumPy .. toctree:: :maxdepth: 2 :caption: Getting Started modules/Introduction modules/Installation modules/License .. toctree:: :maxdepth: 1 :caption: User Guidelines guidelines/BestPractices_and_Pitfalls Config.py Reference .. toctree:: :maxdepth: 1 :caption: Tutorial Stable BL: GABLS1 .. toctree:: :maxdepth: 1 :caption: Performance Benchmarks NVIDIA A100 (80 GB) Hardware Platform Comparison .. toctree:: :maxdepth: 2 :caption: Case Studies examples/CBL_N91/index examples/NBL_A94/index examples/SBL_GABLS1/index examples/SBL_GABLS3/index examples/DC_Wangara/index .. toctree:: :maxdepth: 1 :caption: Model Structure modules/ModelStructure .. toctree:: :maxdepth: 2 :caption: Additional Resources modules/modules Ask a Question ============== Have a question or found a bug? Please open an issue on GitHub: https://github.com/Sukantabasu/jax-alfa/issues Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search`