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Comment by dcolkitt | Hacker News Reader

Matlab sells its onerously expensive licenses by marketing itself as having unbeatable numerics performance. This is mostly a farce.

The vast majority of Matlab's vaunted numerics performance comes from using MKL instead of OpenBLAS. However Intel has made MKL free software. Meaning that you can easily build NumPY on top of it. Numpy+MKL will compile down to virtually identical assembly as Matlab.

There's very little reason in this day and age to pay Mathworks such an insane licensing fee.

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> Matlab sells its onerously expensive licenses by marketing itself as having unbeatable numerics performance.

Not at all. At Lockheed (probably one of Mathwork's biggest customers) the big use case is the toolboxes. Scientific/engineering packages like signal processing, radar, phased array, embedded/VHDL are 2nd to none and are used daily. Some sites also used a lot more of the Simulink side for modeling & simulation.

[0] https://www.mathworks.com/help/signal/ref/signalanalyzer-app...

[1] https://www.mathworks.com/help/comm/examples/rf-satellite-li...

[2] https://www.mathworks.com/help/fusion/examples/multi-patform...

[3] https://www.mathworks.com/products/hdl-coder.html

Only some of the packages are 2nd to none, but as you note some of them like Simulink have large and dedicated userbases. I've heard very mixed results from the VHDL stuff, but some people love it.

Matlab's hook is the domain specific toolkits which don't have polished open source equivalents.

Which ones? They seem pretty overpriced for what you get. IMO Mathematica is a better bet in most cases if you don't want Python or Julia.

A lot of them are very domain specific, like controls engineering and stuff like that.

If I recall, a big chunk of the code that controls Toyota engines is generated from a massive Simulink model.

Simulink is probably the biggest.

Ah. That I would agree with. The rest of the packages don't impress me as much.

For what it's worth, OpenBLAS is not significantly slower than MKL, at least for level 3 linear algebra on x86 on AVX2 downwards. I don't know whether it supports SKX well now, but otherwise BLIS does. (Also OpenBLAS and BLIS are infinitely faster than on POWER and ARM.) I don't understand "compiling down" -- the linear algebra performance is determined by the library, which is, or could be, the same in each case.

[I agree about the marketing aspects and the huge waste of university resources buying into that rather than funding development of free software.]

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