During this session, we'll talk about KMath (https://github.com/mipt-npm/kmath) and more. With Aleksandr, we'll consider different approaches to math API and their realization in different programming languages (Python, C++, Julia, Java and Kotlin). We'll talk about why it's hard to make math both convenient and fast. And take a closer look at the boxing problem.
The audience will see how the context-based approach in Kotlin helps solve not just the balancing problem of speed and convenience but also allows you to make math libraries modular and ensure their compatibility with high-performance platform libraries.
In conclusion, let's talk about the future of math libraries outside C++ (and only in Kotlin).