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Here is the gist of what I want to be able to do.
@generated function gf1(some_func, arg_type1, arg_type2, ..., arg_typeN) optimized_ir = ParallelAccelerator.optimize(some_func, arg_type1, arg_type2, ..., arg_typeN) return optimized_ir end
The problem is that ParallelAccelerator produces an optimized IR for some function for a given set of argument types and then we need to have a Julia method instance created from that IR. Currently, we do this in a really ugly way. We make a stub function and then replace the stub's IR with the optimized IR. This is very fragile and dependent on lots of internal moving parts of Julia. If a