Julia motivation: why weren't Numpy, Scipy, Numba, good enough?

[StefanKarpinski]

@ChrisRackauckas

Of course, I wouldn’t expect well-written type-stable SIMD code to do better, but I think you could get some massive improvements in things like type-unstable code or things with arrays that aren’t strictly typed, and there may be some areas where a tracer kicks in and skips the end of the computation by finding out an analytical solution that may not have been available at compile time.

This sounds a bit like a mix of the proverbial “sufficiently clever compiler” and something that is able to discover that some Vector{Any} actually only ever holds Float64 values and so could be specialized Vector{Float64}. Which sounds like more of a use case for a tracing linter than a tracing JIT. I don’t believe in sufficiently clever compilers but a tracing linter seems like it would be quite useful to have.