Strange Loop Conference
6 HN recommenders · recommended in 6 months, 2021–2025
34:55 · 98K views · Oct 20, 2021
Richard Feldman explains how pure functional languages can match or beat imperative ones on performance. Compilers can turn immutable code into in-place mutation, avoiding naive copying. The talk draws on his work on the Roc language.
Recommended as the clearest explanation of why immutable data need not be slow, and as the introduction to Roc.
8 comments from Hacker News
If you are interested, «why yet another programming language?». The unique selling point of Roc is clever optimization to convert purely functional source code to deep-imperative fast machine code, while keeping all the correctness of functional algorithms. See this video of Richard Feldman for details — «Outperforming Imperative with Pure Functional Languages»: this video Among those clever optimizations: - static reference counting (no GC, like in Rust, but with no borrowing and borrow problems); - stack allocation of the data with no external links; - hidden («opportunistic») mutability even in the cases, where Haskell or Lisp will copy the value.
> Functional programming experts say that their code is efficient because the compiler translates it to an efficient representation on the CPU. They have TCO and other things. But they don't mutate data and hence every function call creates a new data in memory taking up space. How do they overcome that? By letting the compiler make assumptions. For example, consecutive map calls can be converted into a single one. If the data isn't shared with something else, the compiler can mutate it. MUCH easier to paralellize maps. As a starting point for those nitty grittys, this talk is probably as good as any this video
1. Structural sharing - most data doesn't change so you create a copy that reuses much of the original structure 2. Garbage collection and lexical scopes - you clean up memory quickly and in batch 3. Compiler optimizations - you turn functional constructs into imperative ones that reuse and mutate memory at compile-time, where it is provably safe to do so Roc Lang might interest you: this video
> How would one optimize for immutability in this case, other than turning it back into mutability behind the scenes? Roc-lang, which is a functional, systems language in development uses something called opportunistic in-place mutation to do just that. Here's a video where the creator talks about it: this video
We already have many great GC'd functional languages at that performance level. I first learned about Roc from this talk: this video That's a niche that is not currently filled (well, maybe MLTon) and that has me very excited! I'm sure I'm not alone here.