Designing the future of computation the C++ way
Numeric simulations have become a pillar of the Modern Scientific Method, replacing experiments altogether in some fields. Within this new paradigm, people writing science had to quickly change to writing software. As with any new endeavour, this change came with teething problems as few science experts are also expert in software design, development or even research. So called scientific software needs to be fast and developed quickly as the race to publications, patents or viable products is faster than ever. But how can our scientists become efficient in software design? Dynamic languages like Python, Matlab or R fill a niche by allowing non-computer scientists to write software quickly.
So why turn to C++? Well, the resources required to do this kind of computation are not cheap and having to wait for results because software is slow is a bad experience. So why not use our good old, close to the metal, infrastructure language that is C++?
In this talk we will explore why C++, in its latest incarnation of C++20, fits this bill. We will see how designing languages as libraries gives us the best of both worlds: a high level of domain abstractions as well as a high level of performance. We shall see that recent C++ standards draw their power from borrowing powerful concepts from classical languages; concepts such as higher order functions, code as data, and many more.