/sci/ - Science & Math

I've been working on a side project in Julia for the past month.

This is the future of scientific computing for sure. In python, performance was always something in the back of your mind, and figuring out the best ways to offload to numpy or C code became an extra design concern that really slowed things down. Keeping everything in one language reduces a significant cognitive load. Also you rarely have to worry about performance concerns, as Julia is so fucking fast.

The biggest areas to look forward to are in terms of the metaprogramming capabilities and the fact that the JIT is extensible. Automatic differentiation can be built into the language itself, with relatively little code. This is really incredible. To put this in perspective, Google has an entire team of engineers working on modifying the Swift compiler to get automatic differentiation. An insane amount of effort. whereas in Julia, this exact feature can be implemented by a hobbyist in a week or two.