Want faster number-crunching in Python? You can speed up your existing Python code with the Numba JIT, often with only one instruction.

Intel highlights how to achieve high levels of parallelism in large scale Python applications using the Intel Distribution for Python with Numba.

Abe Stern from NVIDIA gave this talk at the ECSS Symposium. "We will introduce Numba and RAPIDS for GPU programming in Python. Numba allows us to write just-in-time compiled CUDA code in Python, ...

The first part of the simplification is to utilise the excellent NUMBA python JIT compiler to allow easy-to-understand code to be deployed as GPU machine code.

IDG Numba uses LLVM to just-in-time-compile numerical code and accelerate its execution. The JIT-accelerated sum2d function completes an execution about 139 times faster than the regular Python code.