The latest annual Python Developers Survey took the pulse of over 30,000 developers to see what makes the community tick in ...

From these low-level interfaces emerged higher-level parallel processing libraries, such as concurrent.futures, joblib and loky (used by dask and scikit-learn) These libraries make it easy for Python ...

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

The head node is connected to a workstation via USB 1.1 allowing the system to be controlled with a Python script. The cluster is configured to process an embarrassingly parallel image convolution.

About 20 years ago engineers around the world began demonstrating what is still the greatest computer innovation of my lifetime, parallel processing. (For more on the concept, visit this course at ...