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Yes sure, that is how OpenMP does; but on the other side: you seem to already do some basic type inference, and building an AST, no? Then you know as well the size and type of your vectors, and can execute actions in parallel if there is enough data to be worth parallelizing. Is there anyone who don't want their code to execute faster if it is possible? Those that do work in big data domain do use threads and vectorized instructions without user having to type in any directive; just import different library. Example, numpy or numpy with cuda backend, or similar GPU accelerated libraries like cudf.
It's a very old project and a VERY basic engine. TBH, engines like godot do a much better job, have their own scripting language (to hide away C++), but still let you write some native code if need be. For TeaScript, I'd be more interested in using it to have a more dynamic pipeline for this project, but performance there is absolutely critical since it can mean the difference between 2 minutes an 2 hours.
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