Numba Explained in 30 Minutes - The Python and Numpy Compiler

Learn about Numba - the Python and Numpy compiler. This tutorial will explain how Numba works, and when and how to use it for numerical algorithms, focusing on how to get very good performance on the CPU.
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Do you have numerical code written in Python and Numpy? Do you wish it ran faster, using the full potential of your CPU?

Then you should try Numba, a JIT compiler that translates a subset of Python and Numpy code into fast machine code.

This talk will explain how Numba works, and when and how to use it for numerical algorithms, focusing on how to get very good performance on the CPU.

To understand this talk, only a basic knowledge of Python and Numpy is needed.

You will also learn when it does and doesn't make sense to use Numba, by contrasting it briefly with some other options for high-performance computing from Python: PyPy, C, C++, Cython, Numexpr, Dask, PyTorch, Tensorflow and Google JAX

#Numba #Python #Morioh

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[IgorKuts]

Christoph, thank you for a great presentation. I am about to use Numba to speed up our various datascience pipelines and your presentation was exactly what I needed.

[hansdietrich]

numba is great. Using it for years already.

[smanzoli]

What I love more in numba is not even jit, it´s CUDA

[CTimmerman]

18:00 Ironic that a comic from a cancelled artist seems to imply that special cases are more important than easy answers.