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Yes, and I think Julia is a perfect starting point for an extremely productive general purpose language.

The one major wart with Julia is reliance on GC, I'm interested to hear what workarounds exist. If no common usage patterns rely on the GC, it should be possible to write "recycling" code that doesn't incur GC pauses and hence, unpredictable latency.

I really enjoy using Julia, it's a great balance of concision, expressiveness, and performance.




There is a common demand from people for extracting just a very concrete computation from a julia codebase and compiling it to a standalone library (or even just using it within an existing julia program, but guaranteeing certain allocation or real time behavior). For example, julia includes a pure julia implementation of libm, but we also maintain the openlibm C library, since we link it into some of our C dependencies that need good quality math functions. It would be nice just to compile the julia version and have it be a drop in replacement for the libm that can be linked. Of course for that you don't want the runtime, or GC or code generator. The challenge here is coming up with the right interfaces and abstractions to make this a feasible and useful thing, without splitting the community into those that care about it and those that don't. We've started some work in this direction, but it isn't really usable yet.


This sounds amazing and exactly what people have been clamoring for. Extremely excited.

I think it will also rocket up Julia's popularity and usage not just for ML but as a general purpose language


Looking forward to have this capability in Julia.

Is some concept of language support for traits/ interfaces and/or static typing part of this effort?

Also, would there be different levels of leanness for the static compile? I can see some people wanting binaries that use a minimal runtime or GC, but no heavy JIT etc so that a larger set of programs can be distributed but at some tradeoff.




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