We will release Linux & Mac OS versions soon.

Great, thank you for the report!

We have just released updated version of toolbox for Windows. It includes bug fix for this issue among other improvements.

Please download it from our homepage (download trial) or just use this link: https://bit.ly/2XwTWH7

Don't forget to copy your license key to the folder of new toolbox version!

Would appreciate if you would test your code with new toolbox and let me know the results. 

Could you please provide minimal, complete, and verifiable example, so that situation can be reproduced?
Please check the top post on the forum homepage: https://mct.userecho.com/

I am not aware of any disadvantages. At least we do not treat AMD any different in our code.

The basic rules is: more CPU cores = higher speed.

If we would compare absolutely equivalent Intel vs. AMD processors (frequencies, number of cores, caches all are the same) - there might be a slight drop in speed if you use Windows.

That is because we use Intel C++ Compiler on Windows, as it produces faster binary code for Intel CPUs.

And, btw, on different platforms performance of all the software packages are different. 

Of course, I would prefer comparison on Windows, as this would be informative for ~80% of users of toolbox.

Why not? I think it is great idea. Also it has sense to extend the tests to cover speed-comparison of FFT and EIG, SVD for special  types of matrices (e.g. banded, Hermitian, complex).

In some if these cases quadruple precision computations in toolbox are faster (at least it was in 2016) than double in MATLAB (in particular solving the banded matrices: https://www.advanpix.com/2016/10/20/architecture-of-eigenproblem-solver/).

The only show stopper for me is (and always has been) significant time and efforts needed to conduct such benchmarks.

I would be happy if somebody would do this (and would help as much as I can). The only suggestion is to use some good many-core CPU, as parallelism is crucially important for matrix computations and FFT.

Ok, great, please keep us updated on your experience with toolbox.

We have just released new version (Windows) with speed-optimized conversion for your case. In our tests speed-up is ~20 times.

Please download and try new trial from our website (our just use this link: https://bit.ly/3mvxXqg ).

Let me know what kind of speed improvement you see in your tests.

Thank you for the details. We are looking into the conversion code to make it faster. Will update you shortly..

Thank you for your question.

Frankly, we didn't expect that conversion to string would be an important part of numerical computations (e.g. running in O(n^2) loop or similar). That is why we didn't optimize it to the maximum extent. I guess your case is very special in this regard.

What do you with the number after conversion (e.g. numeric computations)? I am pretty sure computations will be way more faster compared to vpa.