Integrating with Python
Up until now we have been working with C++ to develop our programs and CUDA kernels, but it can be very useful to leverage all the functionality already available in Python and make everything work together. However, bridging the gap between C++ and Python can feel like introducing two people from completely different social circles — they speak different languages, have different customs, but when they get along, the results can be spectacular. Integrating a GPU-accelerated C++ library with Python can unlock performance benefits while keeping the ease of use and flexibility that Python developers enjoy. Let’s start by exploring why this integration is valuable, the approaches available for making it happen, its potential pitfalls, and how memory management plays a crucial role in the process.
We already known that C++ unleashes raw power and control over hardware, making it the perfect choice for performance-intensive tasks – and...
