Hacker News Reader

so in this case, once say the Julia ecosystem grows then migrate to Julia. or wait for optimizations to be done, e.g have pandas, numpy etc handle multi-core processors etc ?

View on HN

There's quite fundamental optimizations that will be missing if separately compiled pieces cannot optimize together. These barriers disallow many things. Additionally, anything that relies on higher order functions provided by the user, such as optimization or differential equations, will run into issues because those functions cannot be optimized by some super good package developer, but instead have to come from the user.

This blog post highlights the massive performance advantages Julia can have when you start integrating optimized packages and allow for optimizing across these barriers in Julia, and also the pros and cons of allowing these kinds of cross-function optimizations.

https://www.stochasticlifestyle.com/why-numba-and-cython-are...

> or wait for optimizations to be done, e.g have pandas, numpy etc handle multi-core processors etc ?

All those exist already. Indeed, other than DataFrames.jl (the pandas equivalent) they are part of the language itself.

Reply on news.ycombinator.com