Overview: Top Python frameworks streamline the entire lifecycle of artificial intelligence projects from research to ...

In this video from EuroPython 2019, Pierre Glaser from INRIA presents: Parallel computing in Python: Current state and recent advances. Modern hardware is multi-core. It is crucial for Python to ...

Asked on Twitter why a paper is coming out now, 15 years after NumPy's creation, Stefan van der Walt of the University of California at Berkeley's Institute for Data Science, one of the article's ...

Python is powerful, versatile, and programmer-friendly, but it isn’t the fastest programming language around. Some of Python’s speed limitations are due to its default implementation, CPython, being ...

Distributed computing is the simultaneous use of more than one computer to solve a problem. It is often used for problems that are so big that no individual computer can handle them. This method of ...

In this video from the ECSS Symposium, Abe Stern from NVIDIA presents: CUDA-Python and RAPIDS for blazing fast scientific computing. We will introduce Numba and RAPIDS for GPU programming in Python.

IMORTANT INFO ABOUT ANACONDA on HPC: What happened to the Anaconda3 software modules on HPC systems? As of Feb. 1st 2025, RC/HPC will no longer be supplying Anaconda3 modules on the HPC clusters. You ...