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Last active January 2, 2021 12:36
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Julia vs Numpy
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benchmarks.md
Description NumPy (MKL) (sec.) Julia (sec.)
Dot (scalar) product of two 300000 arrays (float64), (1000 loops) 0.03528142820068751 0.027905 (x1/1.3)
Element-wise sum of two 100x100 matrices (int), (1000 loops) 0.0037877704002312385 0.0061 (x1.6)
Element-wise multiplication of two 100x100 matrices (float64), (1000 loops) 0.004193491550176986 0.032161 (x7.7)
L2 norm of 500x600 matrix (float64), (1000 loops) 0.023907507749936486 0.096 (x4)
Matrix product of 500x600 and 600x500 matrices (float64) 0.0018566828504845035 0.01988 (x10.7)
Sort of 500x600 matrix (float64) 0.010326230399914493 0.0161 (x1.6)
@VarLad
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VarLad commented Jan 2, 2021

How about running Julia with MKL too?
I think that's kinda unfair, as MKL is MUCH MORE optimized than OpenBLAS

@VarLad
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VarLad commented Jan 2, 2021

A simple ]add MKL should do the job

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