this post was submitted on 08 Apr 2024
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Rust

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[–] [email protected] 43 points 7 months ago (2 children)

Casey's video is interesting, but his example is framed as moving from 35 cycles/object to 24 cycles/object being a 1.5x speedup.

Another way to look at this is, it's a 12-cycle speedup per object.

If you're writing a shader or a physics sim this is a massive difference.

If you're building typical business software, it isn't; that 10,000-line monster method does crop up, and it's a maintenance disaster.

I think extracting "clean code principles lead to a 50% cost increase" is a message that needs taking with a degree of context.

[–] [email protected] 15 points 7 months ago (1 children)

Yup. If that 12-cycle speedup is in a hot loop, then yeah, throw a bunch of comments and tests around it and perhaps keep the "clean" version around for illustrative purposes, and then do the fast thing. Perhaps throw in a feature flag to switch between the "clean" and "fast but a little sketchy" versions, and maybe someone will make a method to memoize pure functions generically so the "clean" version can be used with minimal performance overhead.

Clean code should be the default, optimizations should come later as necessary.

[–] [email protected] 1 points 7 months ago (1 children)

Keeping the clean version around seems dangerous advice.

You know it won't get maintained if there are changes / fixes. So by the time someone may needs to rewrite the part, or application many years later (think migration to different language) it will be more confusing than helping.

[–] [email protected] 5 points 7 months ago

Easy solution: write tests to ensure equivalent behavior.

[–] [email protected] 5 points 7 months ago

For what its worth , the cache locality of Vec<Box> is terrible in general, i feel like if youre iterating over a large array of things and applying a polymorphic function you're making a mistake.

Cache locality isnt a problem when youre only accessing something once though.

So imo polymorphism has its place for non iterative-compute type work, ie web server handler functions and event driven systems.

[–] [email protected] 16 points 7 months ago (1 children)

Correct me if I am wrong but isn't "loop unrolling/unwinding" something that the c++ and rust compilers do? Why does the loop here not get unwound?

[–] [email protected] 14 points 7 months ago (1 children)

Loop unrolling is not really the speedup, autovectorization is. Loop unrolling does often help with autovectorization, but is not enough, especially with floating point numbers. In fact the accumulation operation you're doing needs to be associative, and floating point numbers addition is not associative (i.e. (x + y) + z is not always equal to (x + (y + z)). Hence autovectorizing the code would change the semantics and the compiler is not allowed to do that.

[–] [email protected] 7 points 7 months ago (1 children)

so if (somehow) the accumulator was an integer, this loop would autovectorize and the performance differences would be smaller ?

[–] [email protected] 4 points 7 months ago

Very likely yes

[–] [email protected] 11 points 7 months ago

Did author knows about difference between static and dynamic dispatch? 🤦🏻‍♂️

[–] [email protected] 7 points 7 months ago (2 children)

It would be interesting to see if an iterator instead of a manual for loop would increase the performance of the base case.

My guess is not, because the compiler should know they are equivalent, but would be interesting to check anyway.

[–] [email protected] 2 points 7 months ago (1 children)

I wonder if the compiler checks to see if the calls are pure and are therefore safe to run in parallel. It seems like the kind of thing the Rust compiler should be able to do.

[–] [email protected] 5 points 7 months ago

If by parallel you mean across multiple threads in some map-reduce algorithm, the compiler will not do that automatically since that would be both extremely surprising behavior and in most cases, would make performance worse (it'd be interesting to see just how many shapes you'd need to iterate over before you start seeing performance benefits from map-reduce). If you're referring to vectorization, then the Rust compiler does automatically do that in some cases, and I imagine it depends on how the area is calculated and whether the implementation can be inlined.

[–] [email protected] 1 points 7 months ago* (last edited 7 months ago) (1 children)

Do you mean this for loop?

for shape in &shapes {
  accum += shape.area();
}

That does use an iterator

for-in-loops, or to be more precise, iterator loops, are a simple syntactic sugar over a common practice within Rust, which is to loop over anything that implements IntoIterator until the iterator returned by .into_iter() returns None (or the loop body uses break).

Anti Commercial AI thingyCC BY-NC-SA 4.0

[–] [email protected] 9 points 7 months ago (2 children)

I think they meant using for accumulating, like this:

shapes.iter().map(Shape::area).sum()
[–] [email protected] 4 points 7 months ago

Yes. That's what I meant.

Though I heavily expect the rust compiler to produce identical assembly for both types of iteration.

[–] [email protected] 2 points 7 months ago (1 children)

Oh, I see. That would be interesting to benchmark too 👍

Anti Commercial AI thingyCC BY-NC-SA 4.0

[–] [email protected] 2 points 7 months ago (1 children)

Anti Commercial AI thingy

Off-topic, but does that actually work? I would assume OpenAI would just ignore it and you'd have to prove that they did so.

[–] [email protected] 5 points 7 months ago (1 children)

Dunno if it works. AI has been tricked into revealing it's training data, so it's possible that it happens and they are sued for using copyrighted material.

This is my drop in the ocean.

Anti Commercial AI thingyCC BY-NC-SA 4.0

[–] [email protected] 2 points 7 months ago (1 children)
[–] [email protected] 3 points 7 months ago (1 children)

Welcome 🙂 A drop more.

Btw, if you're using linux and X11, you can bind a keyboard shortcut to the following shell-script (probably will need to install xte).

#!/usr/bin/env bash
sleep 0.5
xte "str 
Anti Commercial AI thingy"xte "key Return" xte "str [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)" xte "key Return" xte "str
"

Anti Commercial AI thingyCC BY-NC-SA 4.0

[–] [email protected] 3 points 7 months ago (1 children)

I'm on Wayland, but I'm sure I can figure something out.

I do most of my lemmy-ing on mobile, so I'll probably make a bot to auto-edit my posts or something.

[–] [email protected] 3 points 7 months ago

Have fun! I'm curious how you'll do it. If you figure out a way on Wayland, it would be great to read about it!

Anti Commercial AI thingyCC BY-NC-SA 4.0

[–] [email protected] 6 points 7 months ago* (last edited 7 months ago)

I agree with the conclusion, and the exploration is interesting enough that I think it was worth sharing. Still, while the author seemingly knows this already based on their conclusion, it's still worth stressing: these kinds of microbenchmarks rarely reflect real world performance.

This toy case doesn't have many (if any) real world performance-sensitive applications. At best, using shapes in games comes to mind, but shapes there are often represented as meshes, and if you really need the area that much, you might find that precalculating the area once is more impactful on the performance than optimizing how fast the area is calculated.

Still, the author seems aware, and it seems to just be the author sharing their fun experiment.

[–] [email protected] -1 points 7 months ago

No

struct Shapes<const N: usize>([Shape; N])

impl<const N: usize> Shapes<N> {
 const fn area(&self) -> f64 { /* ... */ }
}

Bad article 🤨