Software for in-memory computing is now being developed. Researchers have successfully developed a conversion layer for Python code that allows existing Python code to function with in-memory ...

It is crucial for Python to provide high-performance parallelism. This talk will expose to both data-scientists and library developers the current state of affairs and the recent advances for parallel ...

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.

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, ...

Posted in Software Hacks Tagged python, quantum, quantum computing ← Bringing Guitar Synthesis To The Microcontroller 1920’s Claratone Radio Runs Windows 10 → ...