Eigen sparse matrix support?

[osorensen]

I am creating an R package in which the core computation is to minimize a scalar loss function whose evaluation requires a lot of sparse matrix operations, including the solution of sparse linear systems. I'm using autodiff to compute the gradient and potentially the Hessian, both of which are dense.

Made this work by adding this to the top of autodiff/common/eigen.hpp:

#include <Eigen/SparseCore>

and then this

template<typename Scalar, int Options, typename StorageIndex>
struct VectorTraits<Eigen::SparseMatrix<Scalar, Options, StorageIndex>>
{
  using ValueType = Scalar;


  template<typename NewValueType>
  using ReplaceValueType = Eigen::SparseMatrix<NewValueType, Options, StorageIndex>;
};

I can then define sparse matrices with dual values with something like this:

using llt = Eigen::SimplicialLLT<Eigen::SparseMatrix<dual2nd> >;
using dspmat = Eigen::SparseMatrix<dual2nd>;
using ddiag = Eigen::DiagonalMatrix<dual2nd, Eigen::Dynamic>;

Would it be of interest to include something like this in autodiff itself? I realize things might be harder if the results of differentation are also supposed to be sparse, but when these are dense, it seems quite straightforward.

[osorensen]

Moving to Discussion.