Use the Python version of Google's agent development toolkit to quickly develop AI-powered agents with diverse workflows.

The best parallel processing libraries for Python Ray: Parallelizes and distributes AI and machine learning workloads across CPUs, machines, and GPUs.

AUSTIN, Texas, June 7, 2022 /PRNewswire/ -- Dask, an open-source Python-native parallel computing library, has announced its latest rebrand. Dask's rebranding includes a new visual style ...

Parallel computing is the fundamental concept that, along with advanced semiconductors, has ushered in the generative-AI boom.

Pierre Glaser from INRIA gave this talk at EuroPython 2019. "Modern hardware is multi-core. It is crucial for Python to provide high-performance parallelism. This talk will expose to both ...

And, if we use an interactive Python environment, we can do this kind of scientific analysis in an exploratory way, allowing us to experiment on our data in near real time. Luckily for us, the people ...

That’s where the concept of intermittent computing comes into play, and now thanks to the BFree project, you can develop Python software that persists even when the hardware goes black.

One of the big surprises of the past few years has been the spectacular rise in the use of Python* in high-performance computing applications. With the latest releases of Intel® Distribution for ...

So today’s value in this project lies not in something that you should run out and do yourselves, but instead in what the work tells us about the nuts and bolts of parallel processing architecture.