#Python fluidsim examples code

We’d like to have a nice, simple and unified API for these two modes.ĪOT is useful to be able to distribute compiled packages and in some cases, In modern Python, we have nice syntaxesĪhead-of-time (AOT) and just-in-time (JIT) compilation modes are both useful. In mostĬases, the benefice of writting big compiled extensions (with Cython or inĪdding types is sometimes necessary. Python and its interpreters are good for the rest. Let’s accelerate/compile only what needs to be accelerated, i.e. ForĮxample, with Transonic, we are able to accelerate (simple) methods ofĬlasses even though some accelerators don’t support classes.

#Python fluidsim examples code

Let’s try to keep the code as it would be written without acceleration. There are many tools to accelerate Python-Numpy code! Let’s avoid writtingĬode specialized for only one of these tools. Pythonic way, with decorators and context managers. To express that a function, a method or a block of code has to be accelerated Not the special hacks we want to use to make it fast. Let’s try to write universal code which express what we want to compute and However, there are tools toĪccelerate such Python-Numpy code which lead to very good performances! Pythonic, readable, modern code (Python >= 3.6).

We’d like to write scientific / computing applications / libraries with Transonic targets Python end-users and library developers. Overview of the Python HPC landscape and zoom on Transonic. Make your numerical Python code fly at transonic speed (EuroScipy 2019), The context of the creation of Transonic is presented in these documents: However, Transonic is now really usable, useful and used “in production” inįluidSim and FluidFFT (see examples for The long-term project Transonic is still in an active development stage (see our roadmap). You can try Transonic online by clicking this button. Transonic run fine without any accelerators installed (of course without

The accelerators are not hard dependencies of Transonic: Python codes using Transonic is a pure Python package (requiring Python >= 3.6) to easilyĪccelerate modern Python-Numpy code with different accelerators (currentlyĬython, Pythran and Numba, but potentially later Cupy, PyTorch, JAX, Weld, Pyccel, Uarray, etc…).