[Numpy-discussion] performance solving system of equations in numpy and MATLAB

[Nathaniel Smith]

What operating system are you on and how did you install numpy? From a
package manager, from source, by downloading from somewhere...?
On Dec 16, 2015 9:34 AM, "Edward Richards" <edwardlrichards at gmail.com>
wrote:

> I recently did a conceptual experiment to estimate the computational time
> required to solve an exact expression in contrast to an approximate
> solution (Helmholtz vs. Helmholtz-Kirchhoff integrals). The exact solution
> requires a matrix inversion, and in my case the matrix would contain ~15000
> rows.
>
> On my machine MATLAB seems to perform this matrix inversion with random
> matrices about 9x faster (20 sec vs 3 mins). I thought the performance
> would be roughly the same because I presume both rely on the same LAPACK
> solvers.
>
> I will not actually need to solve this problem (even at 20 sec it is
> prohibitive for broadband simulation), but if I needed to I would
> reluctantly choose MATLAB . I am simply wondering why there is this
> performance gap, and if there is a better way to solve this problem in
> numpy?
>
> Thank you,
>
> Ned
>
> #Python version
>
> import numpy as np
>
> testA = np.random.randn(15000, 15000)
>
> testb = np.random.randn(15000)
>
> %time testx = np.linalg.solve(testA, testb)
>
> %MATLAB version
>
> testA = randn(15000);
>
> testb = randn(15000, 1);
> tic(); testx = testA \ testb; toc();
>
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>
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