> The main limitation is the prohibition of dynamic dispatch. This is a key feature of Julia, where methods can be selected at run time based on the types of function arguments encountered. The consequence is that most public packages don't work, as they may contain at least some instances of dynamic dispatch in contexts that are not performance-critical. Some of these packages can and will be rewritten so that they can be used in standalone binaries, but, in others, the dynamic dispatch is a necessary or desirable feature, so they will never be suitable for static compilation.
The problem (which the author didn't focus on, but which I believe to be the case) that Julia willingly hoisted on itself in the pursuit of maximum performance is _invoking the compiler at runtime_ to specialize methods when type information is finally known.
Method dispatch can be done statically. For instance, what if I don't know what method to call via abstract interpretation? Well, use a bunch of branches. Okay, you say, but that's garbage for performance ... well, raise a compiler error or warning like JET.jl so someone knows that it is garbage for performance.
Now, my read on this work is the noble goal of prying a different, more static version of Julia free from this compiler design decision.
But I think at the heart of this is an infrastructural problem ... does one really need to invoke the compiler at runtime? What space of programs is that serving that cannot be served statically, or with a bit of upfront user refactoring?
Open to be shown wrong, but I believe this is the key compiler issue.
In performant Julia code, the compiler is not invoked, because types are statically inferred. In some cases you can have dynamic dispatch, but that doesn't necessarily mean that the compiler needs to run. Instead you can get runtime lookup of previously compiled methods. Dynamic dispatch does not necessitate running the compiler.
Perhaps there is something about subtyping which makes this answer ... not correct -- and if someone knows the real answer, I'd love to understand it.
I believe that this answer is because of performance -- if I can JIT at runtime, that's great -- I get dynamism and performance ... at the cost of a small blip at runtime.
And yes, "performant Julia code" -- that's the static subset of the language that I roughly equated to be the subset which is trying to be pried free from the dynamic "invoking the compiler again" part.
Anyway, performance in Julia relies heavily on statically inferring types and aggressive type specialization at compile time. Triggering the compiler later, during actual runtime, can happen, but is certainly not beneficial for performance, and it's quite unusual to claim that it's central to the performance model of Julia.
If you are asking why Julia allows recompiling code and has dynamic types, it's not for performance, but to allow an interactive workflow and user friendly dynamism. It is the central tradeoff in Julia to enable this while retaining performance. If performance was the only concern, the language would be very different.
You claimed:
> Allowing invokation of the compiler at runtime is definitely not something that is done for performance, but for dynamism, to allow some code to run that could not otherwise be run.
I asked:
> why not just compile a static but generic version of the method with branches based on the tags of values? ("Can't figure out the types, wait until runtime and then just branch to the specialized method instances which I do know the types for")
Which can be done completely ahead of time, before runtime, and doesn't rely on re-invoking the compiler, thereby making this whole "ahead of time compilation only works for a subset of Julia code" problem disappear.
Do you understand now?
My original comment:
> The problem (which the author didn't focus on, but which I believe to be the case) that Julia willingly hoisted on itself in the pursuit of maximum performance is _invoking the compiler at runtime_ to specialize methods when type information is finally known.
is NOT a claim about the overall architecture of Julia -- it's a point about this specific problem (Julia's static ahead-of-time compilation) which is currently highly limited.
Secondly, I think it's on you to clarify that you were talking specifically and exclusively about static compilation to standalone binaries. Re-reading your first post strongly gives the impression that you were talking about the compilation strategy in general.
I would also remind you that Julia always does does-ahead-of-time compilation.
Furthermore, my limited understanding of the static compiler (--trim feature), based on hearsay, is that it does pretty much what you are suggesting, supporting dynamic dispatch as long as one can enumerate all the types in advance (though requiring special implementation tricks). Open-ended type sets are not at all supported.
This is exactly what the new AOT compiler (juliac) does. The original article is just a bit inaccurate.
The problem though, is that if you have a truly dynamic call-site where you have no idea which method body will be called, then the AOT compiler can't know if the right method specializations will survive the trimming process, so you'll get errors or warnings when compiling with the --trim feature active (--trim is what is used to make the AOT compiled binaries small).
However, there are still lots of cases where you can have a dynamic dispatch but can convince the compiler that there will be an already compiled method signature for every possible specialization. In that case --trimm will work fine and do exactly what you described above.
lol
ekjhgkejhgk•2mo ago
Julia's multiple dispatch is really powerful. In my opinion it's great user experience for implementing generic code.
It has a downside: since you don't know at build-time what types you'll shove inside your functions, you don't know what to compile.
But some times the user does know. What does this, according to my understanding, is that if you tell the compiler what types you'll be using it can compile everything ahead of time.