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julia-numpy-fortran-test reviews and mentions
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Optimized Rust Is Stil Slower Than Python+NumPy
No surprise, because NumPy is implemented with Fortran which is designed to be efficient and fast at mathematical operations. Rust is not. And Python is not either, which is why it uses Fortran under the covers.
I wouldn't be surprised to Rust numerical libraries created similar to NumPy which also use Fortran, for the same reasons.
If you want a real comparison, try NumPy vs Julia:
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Julia: Faster than Fortran, cleaner than Numpy
Is the python code missing a square root?
https://github.com/mdmaas/julia-numpy-fortran-test/blob/main...
For fun I ran in Matlab with a 2.9 GHz i7-7820HQ and get about 1.83s for N=10,000 single threaded.
A = exp((k*1i)*sqrt(a.^2 + (a.^2)'))
Stats
mdmaas/julia-numpy-fortran-test is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of julia-numpy-fortran-test is Fortran.