[qsort]

That's a cool idea. I don't know how realistic it is to achieve performance parity, but the "generic" functionality is definitely intriguing.

[adgjlsfhk1]

The initial results are that libraries like LoopVectorization can already generate optimal micro-kernels, and is competitive with MKL (for square matrix-matrix multiplication) up to around size 512. With help on macro-kernel side from Octavian, Julia is able to outperform MKL for sizes up to to 1000 or so (and is about 20% slower for bigger sizes). https://github.com/JuliaLinearAlgebra/Octavian.jl.