cargo-call-stack VS samsara

Yes, it's what I wrote about in the last paragraph. If you can compute maximum stack size of a function, then you can avoid dynamic allocation with fibers as well. You are right that such implementations do not exist in right now, but I think it's technically possible as demonstrated by tools such as https://github.com/japaric/cargo-call-stack The main stumbling block here is FFI, historically shared libraries do not have any annotations about stack usage, so functions with bounded stack usage would not be able to use even libc.

For rust code, I have found https://github.com/japaric/cargo-call-stack to be the best available option, as it does take advantage of how Rust types are implemented in LLVM-IR to handle function pointers / dynamic dispatch a little better. An even better solution would try to use MIR type information as well to further narrow down targets of dynamic calls in a Rust-specific way, but no such tool exists that I know of.

cargo-call-stack Static stack analysis!

Generators can just dump stuff on the stack. They have additional their own stack for storing their state. If you can prove an upper amount of creation of generators in the call graph, that would however work. There is for example this nice tool for Rust doing the overapproximation.

Not easy at all.

I know that in the small-embedded world, people do work on such things.

Eg https://github.com/japaric/cargo-call-stack

> IME it's the other way around, per-object individual lifetimes is a rare special case

It depends on your application domain. But in most cases where objects have "individual lifetimes" you can still use reference counting, which has lower latency and memory overhead than tracing GC and interacts well with manual memory management. Tracing GC can then be "plugged in" for very specific cases, preferably using a high performance concurrent implementation much like https://github.com/chc4/samsara (for Rust) or https://github.com/pebal/sgcl (for C++).

> Just for example: "it needs a GC" could be the heart of such an argument

Rust can actually support high-performance concurrent GC, see https://github.com/chc4/samsara for an experimental implementation. But unlike other languages it gives you the option of not using it.

The compiler support you need is quite limited. Here's an implementation of cycle collection in Rust: https://github.com/chc4/samsara It's made possible because Rust can tell apart read-only and read-write references (except for interior mutable objects, but these are known to the compiler and references to them can be treated as read-write). This avoids a global stop-the-world for the entire program.

Cascading deletes are rare in practice, and if anything they are inherent to deterministic deletion, which is often a desirable property. When they're possible, one can often use arena allocation to avoid the issue altogether, since arenas are managed as a single object.

There are concurrent GC implementations for Rust, e.g. Samsara https://redvice.org/2023/samsara-garbage-collector/ https://github.com/chc4/samsara that avoid blocking, except to a minimal extent in rare cases of contention. That fits pretty well with the pattern of "doing a bit of GC every frame".

There are a number of efforts along these lines, the most interesting is probably Samsara https://github.com/chc4/samsara https://redvice.org/2023/samsara-garbage-collector/ which implements a concurrent, thread-safe GC with no global "stop the world" phase.

Nice blog post! I also wrote a concurrent reference counted cycle collector in Rust (https://github.com/chc4/samsara) though never published it to crates.io. It's neat to see the different choices that people made implementing similar goals, and dumpster works pretty differently from how I did it. I hit the same problems wrt concurrent mutation of the graph when trying to count in-degree of nodes, or adding references during a collection - I didn't even think of doing generational references and just have a RwLock...