Pyhton projects can perform fast algebraic calculations with low overhead using the new Nvidia library for Cuda-X.

For Python, Nvidia recommends version 3.9 and higher. The binaries on PyPI are built with CUDA 12 and require CUDA drivers from 525.60.13 (Linux x86-64) or 528.33 (Windows x86-64).

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, ...

Today Nvidia announced that growing ranks of Python users can now take full advantage of GPU acceleration for HPC and Big Data analytics applications by using the CUDA parallel programming model.

Although Nvidia fully backs RISC-V as a legitimate CPU architecture, it isn't ready to bring CUDA to other third-party processors yet.