What garbage collection actually costs
shivanshuag.com23 points by shivanshuag 4 days ago
23 points by shivanshuag 4 days ago
> Think of a service that keeps a large cache in memory, or an index built out of millions of small objects that all point at each other. Every one of those pointers has to be followed on every cycle, for as long as the process is up.
That's a strange thing to assert, having acknowledged the existence of generational GC.
It occurs to me that I have never seen any description of generational GC that actually notes how that works, though.
If we have two generations, young and old, we obviously can't simply "just collect in the young generation" — which I feel like is exactly what most generational GC descriptions say. If we only traced young objects, we could very well miss an old object pointing at a young one, collect the younger object, and now we've got a dangling pointer.
So there must be some book-keeping to avoid tracing everything (or what'd be the point of generations), but I have no idea of what that book-keeping is, or its cost.
> Show me your code and conceal your data structures, and I shall continue to be mystified. Show me your data structures, and I won't usually need your code; it'll be obvious.
Similarly, the statement
> Reference counting also has its own running cost, paid on every copy of a pointer you make and every time you drop one.
isn’t 100% true. It’s not necessarily on every copy or drop. Compilers can (and do) elide reference count updates if they can proof they aren’t needed, and can even skip allocating room for reference counts if they can proof it isn’t needed (example: a local object that doesn’t escape its scope)
I also find it a miss that the article doesn’t discuss memory usage. A garbage-collected program needs more memory to match the performance of the equivalent manually managed language.
https://dl.acm.org/doi/10.1145/1094811.1094836 says you need to give it 5 times the memory, but that’s from 2005 and likely outdated.
In 1990s C++ we did:
void foo::method(const &smart_ptr<thing> x) { ... }
Even things built directly on underlying malloc and free typically have some form of "garbage collection" in the malloc implementation for efficiency and performance (geometric sizing, thread caching, etc).
It's best to think about lifetimes and lifecycles where possible. Immutability where sensible and things like pool allocation are examples of this.
GC languages can result in quite pessimistic code because they encourage people to NOT think about what is going on. But people have also built functional HFT engines on things like the JVM by thinking about lifetimes and lifecycles.
Ultimately, the entire problem of deallocation in general is a continuum, not a binary, and I tend to find it hard to take anyone seriously who is vigorously arguing about how awful GC is if they don't understand that and indicate some understanding of the concept. The closest you can get to real "manual" memory management on a modern system is to use nothing but arena allocations, and if you really want "manual" memory management, you need to allocate some small fixed number of arenas, because if you're constantly allocating and deallocating them that is itself probably an automated process that could go wrong, at least in theory. Malloc/free or new/delete isn't really "manual memory management".
The wide variety of options and tradeoffs, with fewer clear lines in the sand than most people seem to think, is already enough to call it a "continuum" but what really finishes the job is that they're all mixable and matchable. Something like Zig makes that really obvious, but most static languages have at least some sort of ability to mix in multiple strategies. There's nothing wrong with a C++ program that uses new & delete, and also uses arenas for some things, and also uses garbage collection for some things, and also has an integrated scripting language like Lua with its own memory strategies. Such programs are not that uncommon... that describes modern games nowadays, the supposed canonical case where you "can't afford GC". But it can... it just fences it in to a particular domain where it fits.
Agreed, for most real world softwares, the cost of GC is irrelevant. But there are still some programs like databases or game engines where the cost can start adding up. That's when you measure and optimize.
Yet the three major game engines Unreal, Unity and Godot all have a GC on their infrastructure, and Capcom is quite happy with their .NET fork on RE Engine.
Also every single graphics application that uses Metal or DirectX, relies on reference counting as GC algorithm.
I’m sure those three engines have had no issues with performance whatsoever right?
Oh shit…
Game developers are always trying to push the boundaries. The only game engines without performance issues are ones hardly being used.
Do you have any source taking about GC caused performance issues in those engines?
Too many to post, you can just google “{engine} gc spike” for example.
Heck, there is a whole cottage profession of experts who get called into fix GC related performance issues with Unity.
So are you saying this cottage industry achieves success or the industry formed around an impossible task?
A cottage industry is built around making rocks look good too. Is that an indicator that games are good or bad at making rocks?
> That's when you measure and optimize.
How do you "optimize" the GC away after you wrote your entire database server in a language that uses it?
It's incredibly in common in game development, C# has a lot of features you can take advantage for this.
But the most naive example any language supports is simple object pooling.
Then more fancy, zero allocations tasks in C# https://github.com/cysharp/unitask
Starting by using a GC language that is strongly typed, compiles to native code, supports value types, memory pools/arenas if required, which provides best of both worlds.
Where GC means any kind of GC algorithm from CS point of view.
Object pooling and bump allocators using persistent scratch buffers, mostly. The latter what you'd use for read buffers in I/O intensive applications like databases and the like.
GC languages typically have features of the language and/or standard library that make GC the default, not the only option.
What doesn't save you from having to rewrite the entire system.
(Even though, no, that's not typical. That's a tiny minority of them.)
Not sure I understand the question, but it generally works like this:
Once you measure, you'll find a small fraction of the code is taking a large fraction of the time. When you zoom in on trouble-spots you may find, e.g. that the GC is taking the time (or you may find something else entirely is taking the time). If it's the GC, you might look and see, e.g., that it's spending its time tracing the objects in the 100K node graph you're creating several times a second, and realize you could, e.g., create it once and simply keep reusing it. Perhaps it might be as simple as using removeAll(keepingCapacity: true) instead of removeAll() (a Swift example).
The superficial details differ, but you generally just want to understand what the GC is working so hard on and lighten its load. If you haven't been measuring and optimizing throughout, there are almost certainly easy-to-pluck, low-hanging fruits, ripe for the taking.
This assumes that you’re only ever running a single software at a time. Sure, 2-10x slower/memory consumption might not matter in a vacuum, but when every software is like this, you get machines that feel slower than they did 2 decades ago.
I used to write a lot of Javascript-like Extendscript scripts back when I was using InDesign a lot. The DOM's global object $ had a method to directly invoke the garbage collector. It made a difference certainly, but it was difficult to tell to what extent because InDesign itself gradually leaks memory and becomes more bloated the longer you use it in a single session.
> In Rust you pay for it by arranging your program in a way the compiler can verify.
I disagree with this. The sentence implies that this work is done in order to make the compiler happy, where my experience is that it forces the programmer to actually get it right.
I had an "aha moment" when I was frustrated at failing to express my intent to the compiler, and suddenly realised that the reason I couldn't "just say the magic words" was that my object ownership design was inherently flawed. I had to make large changes not to make the compiler happy, but to actually have a coherent design.
So no, it's not about what "the compiler can verify". That's like saying "my lawyer won't let me do this". No, your lawyer is your employee, not your boss. They're just saying that if you do this, then you may go to prison. It's not the same thing.
("unsafe" is the Rust way to go "thank you, legal department, but I'm making a business decision to take this risk. Your concern has been noted")
I understand what you’re saying, but I read that phrase in a different way.
Let’s say you have two ways of doing the same thing: both work, both are legit and neither introduce GC bugs. The only difference between the two is that one can be verified by the compiler while the other can’t, so you are stuck with solution no. 1 although both would work.
To phrase it differently: the code that gets verified by the compiler is safe, but is all safe code verifiable by the compiler?
I’m not implying that’s the case, but that’s what I feel the author is saying.
> To phrase it differently: the code that gets verified by the compiler is safe, but is all safe code verifiable by the compiler?
Right. And this reduces to the halting problem, so in theory the compiler cannot know that all safe code is safe.
In practice, I'm saying that not just syntactically, but in your code's design, the compiler is more likely to be right. It's a bit like Chesterton's fence. You can bypass the lifetime checks if you just have the confidence to say "yes, I'll use `unsafe` here and it's fine because these reasons". As you're writing your "SAFETY" comment, you may very well find yourself not so confident anymore. And indeed, often this compiler-induced "stop and think" prevented you steaming ahead with a bug.
Now, the borrow checker is not perfect. I don't know how far away from "all but NP-complete cases" it is. My experience is that it's almost always right, and I've only had to put a seemingly needless "drop" statement to placate it. But they're working on it. A new one is coming: https://daily.dev/posts/rust-s-new-borrow-checker-is-coming-...
And once again this old blog post of mine comes to mind: https://blog.habets.se/2020/12/Bypassing-safety-check-for-ob...
In any case "by arranging your program in a way the compiler can verify" I think is not accurate, because the overlap between "correct" and "compiler can verify" is nearly complete, though yes the latter is a strict subset of the former. In other words I don't write Rust to make the compiler be able to verify it, but to make it correct. And nearly always that means the compiler can verify it too.
I've had that moment in Rust too, where there was no composition that effected what I wanted, because supporting that model would have meant a very different backing data structure. However in that case I actually didn't care about the kind of correctness problem it was saving me from.
I've also had the converse experience, where I know full well that the structure I'm trying to impose is correct and quite efficient, but its part of the space that rust doesn't cover.
Rust is great. It's a noble attempt to bring a degree of correctness to a problem space that suffers from a great deal of slop. But to pretend that the model is complete, or that the design decisions that were made are perfect in every way, is just wrong. That the rust compiler and runtime can't support my construct isn't really an absolute value judgement on that idea in the first place. The rust compiler isn't really an oracle that tells you whether something is right or not in an arbitrary value system.
Right. The borrow checker is not always right. Just almost always right. It's not perfect (because halting problem), but… well I already said the rest in https://news.ycombinator.com/item?id=49287460
Still, I don't write Rust code the way I do "to make the compiler happy", but to make it correct. And sometimes it's correct to drop some "unsafe" because gosh darn it, you know it's fine this time.
And you're probably right for the cases you're thinking of, where Rust wouldn't let you (at least without unsafe). And maybe you're 99% sure about that.
But for every 100 changes we’re 99% sure won’t cause an outage, one will…
(also future changes may invalidate assumptions you relied on, of course, making it no longer true)
Do you have some examples you can share where you think Rust prevents you doing the right thing? The ones I run into tend to force me to think of the edge cases, and usually those edge cases don't even have a right answer.
this one may actually be solvable, but I kinda timed out on it. okay, so I'm doing distributed systems, and my primary abstraction is a large stream that I'm using to connect components across machines. its kind of mandatory that I implement back pressure for these streams, because awful things can happen if I don't.
ok, I have a large local container of records that I want to stream over a back pressured channel. now we clearly have a problem that the iterator needs to be long lived, and I don't really want to serialize all accesses to the collection for a streaming operation that may never terminate.
for this particular domain I don't actually care about serializability of the iterators view of the collection. I clearly don't want the container to be left in an erroneous or inconsistent state, but otherwise anything goes.
all the iterators for all the standard rust containers have lifetimes bounded by the container (batch), and because they all represent internal state, they all have to be mutable. and in this case they need to be async also.
I don't think there is an 'idiomatic' way to represent that access pattern, and it kind of necessitates writing ones own container. if there is a good answer to this I'd be curious to hear it, but I consider this one of the major personal failure modes for rust, which is 'oh, yeah, well, in order to figure that out to need to understand [long list of compiler instristic property types and runtime behaviour], which isn't super pragmatic.
since I'm here, I've already wasted words here talking about the dismal async situation, but I think more important to me as a systems programmer is the lifetime abstraction. It think its great to put a name to it and try to put rules around lifetimes - these are traditionally implicit things that we reason about _outside the program text_, and that's a real bother. however everything I do is state management, and the lifetimes of those states (files, connections, higher level sessions) don't directly correspond to the lexical calling stack. the only tools that rust gives me is Arc, which some with a whole set of busy caveats, or trying to thread several lifetimes through the entire call path - a road that I've been down and abandoned for readability and maintenance.
now you can argue that rust would prefer that I use a thread per object, and while that might be workable, that a pretty strong and side-effecting constraint to apply to all of the programs in my domain.
What does GC cost? For Caddy with an incredibly synthetic http only benchmark it costs about 2ms of latency and somewhat less throughput. Worth it in an incredibly artificial benchmark? Perhaps. However when it comes to real world usage the cost is a significantly smaller piece of the pie.
Not really the point of the post, but there is a third memory allocation paradigm where you can do manual allocations and deallocations, but without the mental overhead of having to remember to free memory because the compiler will force you to properly handle it. Mojo has linear type support so you can do something like this: https://x.com/melodyogonna/status/2085089269484343725?s=20
Props for using a correct nomenclature. Reference counting is a "kind of automatic garbage collection. Tracing garbage collection is also a kind of automatic garbage collection.
This is one of the best high-level survey explanations of GC I have seen, nice work.
There's a third way here. It could be called many things: Single ownership by default, automatic stack lifetimes, hidden unique pointers, etc. The main idea is that the lifetime of dynamic heap data is treated no differently to primitive stack data: Clean it when it goes out of scope. Rust and C++ require you to specify this manually, but Nim is unique among native-compiled languages in that is does it by default, with tools to opt-out. An advantage of this approach is that combining immutable values and static analysis can reduce most parameter passing to borrows, again, without needing the programmer to specify, by default. The main cost being that some assignments, especially crossing the variable-to-immutable line or vice-versa, would require a copy.
I rarely see a real use case bottle necked on garbage collection.
There is no need for garbage collection if you don’t form circular references. Just have a canonical direction and always keep weak references the other way.
Reference counting is a different model. Many papers have explored the differences and similarities, and your comment leaves so much out that it cannot even be said to be true or false.
I'd say GC is always the fastest to free objects within the main code path. Literally zero instructions.
> I'd say GC is always the fastest to free objects within the main code path. Literally zero instructions
True, but reference counting or free need not be far behind. They can append the pointer being freed to a per-thread list (⇒ no locking needed) that a separate thread that does the actual freeing periodically claims and then iterates over to actually free the objects.
Disadvantage is that memory usage goes up a bit because the actual freeing is delayed, but that (likely) is less so than with a garbage collector.
GC, zero instructions: that's funny; JVM used to "stop to world" to process that zero instructions;
I was explicitly talking about exactly one very specific part a way to implement GC.
It was very clear that I was not talking about the active parts of the garbage collection.
It's really cheap to produce garbage.
It doesn't leave anything relevant out.
Java pioneered this garbage collection stuff because you had cycles of references. You don't need to have cycles. WeakRef is a much better thing now. All you need is reference counting, and you don't need any garbage collection at all. When the reference count reaches 0, you destroy the object and free up its memory. It's far more predictable than GC, too.
And GC isn't "the fastest" to free objects, it has to walk a graph. The fastest is actually arena allocation and then just dropping the whole thing. But that's exactly what owning an entire container of objects can do. If you have a doubly linked list, for example, A[n] -> A[n+1] but also A[n+1] -> A[n] but neither of those should be a strong reference to prevent reclaiming. Instead, the container of that doubly linked list should be the one having a strong reference to its items.
I understood your first comment without expanding on it like this. You also don't need to explain what reference counting is.
> GC isn't "the fastest" to free objects, it has to walk a graph.
No, you don't inherently need to. And what I said is that it's super duper fast to produce garbage. I did not say that actually freeing the underlying memory, or any other cleanup, was fast.
I'm not even arguing for GCs, here. I even think GC languages tend to become tech debt generators, as garbage is not addressed until it's a really complex problem with no good solutions.