After more than three years of efforts, Eigen 3.3 has been released today, on November 10, 2016.
Those include, a novel evaluation mechanism  of expressions, support for AVX, FMA, AVX512, VSX and ZVector vector instructions, unaligned vectorization, nvcc/CUDA, more OpenMP parallelism , a fast divide and
conquer SVD algorithm , a CompleteOrthogonalDecomposition class for fast minimal norm solving , a LS-CG solver , a fast reciprocal condition number estimators in LU and Cholesky factorizations, LU::transpose()/adjoint() API , support for inplace
decompositions , support for matrix-free iterative solvers , new array functions , support for any BLAS/LAPACK libraries as backend , improved support for mixing scalar types , eigenvectors in GeneralizedEigenSolver, a complete rewrite of
LinSpaced , a non officially supported but massively used Tensor module with CUDA and OpenCL support , and more .