These are not the same.
The problem with GC'd systems is that you don't know when the GC will run and eat up your cpu cycles. It is impossible to determine when the memory will actually be freed in such systems. With ARC, you know exactly when you will release your last reference and that's when the resource is freed up.
In terms of performance, ARC offers massive benefits because the memory that's being dereferenced is already in the cache. It's hard to understate how big of a deal this is. There's a reason people like ARC and stay away from GC when performance actually begins to matter. :)
It's more like "you notice when it happens". You don't know in advance when the last reference will be released (if you did, there would be no point in using reference counting).
> In terms of performance, ARC offers massive benefits because the memory that's being dereferenced is already in the cache.
It all depends on your access patterns. When ARC adjusts the reference counter, the object is invalidated in all other threads' caches. If this happens with high frequency, the cache misses absolutely demolish performance. GC simply does not have this problem.
> There's a reason people like ARC and stay away from GC when performance actually begins to matter.
If you're using a language without GC built in, you usually don't have a choice. When performance really begins to matter, people reach for things like hazard pointers.
A barista knows when a customer will pay for coffee (after they have placed their order). A barista does not know when that customer will walk in through the door.
> (if you did, there would be no point in using reference counting).
There’s a difference between being able to deduce when the last reference is dropped (for example, by profiling code) and not being able to tell anything about when something will happen.
A particular developer may not know when the last reference to an object is dropped, but they can find out. Nobody can guess when GC will come and take your cycles away.
> The cache misses absolutely demolish performance
With safe Rust, you shouldn’t be able to access memory that has been freed up. So cache misses on memory that has been released is not a problem in a language that prevents use-after-free bugs :)
> If you’re using a language without GC built in, you usually don’t have a choice.
I’m pretty sure the choice of using Rust was made precisely because GC isn’t a thing (in all places that love and use rust that is)
Sorry, no chance of deciphering that.
> There’s a difference between being able to deduce when the last reference is dropped (for example, by profiling code) and not being able to tell anything about when something will happen.
> A particular developer may not know when the last reference to an object is dropped, but they can find out.
The developer can figure out when the last reference to the object is dropped in that particular execution of the program, but not in the general sense, not anymore than they can in a GC'd language.
The only instance where they can point to a place in the code and with certainty say "the reference counted object that was created over there is always destroyed at this line" is in cases where reference counting was not needed in the first place.
> With safe Rust, you shouldn’t be able to access memory that has been freed up. So cache misses on memory that has been released is not a problem in a language that prevents use-after-free bugs :)
I'm not sure why you're talking about freed memory.
Say that thread A is looking at a reference-counted object. Thread B looks at the same object, and modifies the object's reference counter as part of doing this (to ensure that the object stays alive). By doing so, thread B has invalidated thread A's cache. Thread A has to spend time reloading its cache line the next time it accesses the object.
This is a performance issue that's inherent to reference counting.
> I’m pretty sure the choice of using Rust was made precisely because GC isn’t a thing (in all places that love and use rust that is)
Wanting to avoid "GC everywhere", yes. But Rust/C++ programs can have parts that would be better served by (tracing) garbage collection, but where they have to make do with reference counting, because garbage collection is not available.
but it also has big disadvantage, that it communicates to actual malloc for memory management, which is usually much less performant than GC from various reasons.
Can you elaborate?
I've seen a couple of malloc implementations, and in all of them, free() is a cheap operation. It usually involves setting a bit somewhere and potentially merging with an adjacent free block if available/appropriate.
malloc() is the expensive call, but I don't see how a GC system can get around the same costs for similar reasons.
What am I missing?
- A moving (and ideally, generational) GC means that you can recompact the heap, making malloc() little more than a pointer bump.
- This also suggests subsequent allocations will have good locality, helping cache performance.
Manual memory management isn't magically pause-free, you just get to express some opinion about where you take the pauses. And I'll contend that (A) most programmers aren't especially good at choosing when that should be, and (B) lots (most?) software cares about overall throughput, so long as max latency stays under some sane bound.
I've seen some benchmarks, but can't find them now, so maybe I am wrong about this.
> free() is a cheap operation. It usually involves setting a bit somewhere and potentially merging with an adjacent free block if available/appropriate.
there is some tree like structure somewhere, which then would allow to locate this block for "malloc()", this structure has to be modified in parallel by many concurrent threads, which likely will need some locks, meaning program operates outside of CPU cache.
In JVM for example, GC is integrated into thread models, so they can have heap per thread, and also "free()" happens asynchronously, so doesn't block calling code. Additionally, malloc approaches usually suffer from memory fragmentation, while JVM GC is doing compactions all the time in background, tracks memory blocks generations, and many other optimizations.
