Re: [eigen] cppduals - dual number implementation with Eigen specializations

[Brad Bell <bradbell@xxxxxxxxxx>]

Have you fixed the problem of short cutting operations in eigen sparse matrix routines; see
https://eigen.tuxfamily.org/bz/show_bug.cgi?id=1480

On 12/3/19 6:36 AM, Michael Tesch wrote:
> Hello,
>
> I've written (yet another!) Dual Number implementation for automatic differentiation.  It is meant 
> to be used as the value-type in Eigen matrices, and has templates for vectorization (shockingly) 
> similar to (and based on) Eigen's complex-type vectorizations.  It is quite fast for first-order 
> forward diff, and imho pretty easy to use.  There are also SSE/SSE3/AVX vectorizations for 
> std::complex<dual< float | double >> types.
>
> The library is here: https://gitlab.com/tesch1/cppduals , and there's a small paper in JOSS too: 
> https://doi.org/10.21105/joss.01487
>
> I hope this could be useful for someone and would be glad for any feedback, improvements, etc.
>
> It would be interesting to compare this approach to others, by hand-wavey arguments I believe it 
> should ultimately be faster in certain cases.
>
> Cheers,
> Michael