Special Matrices

Currently cuNumeric only supports LinearAlgebra.Diagonal. Other special matrix types like Tridiagonal and Symmetric will follow.

Diagonal matrices are common, require only storage of the diagonal elements and are often simple to compute operations on (i.e. LinearAlgebra.inv). LinearAlgebra.Diagonal matrices can be constructed from 1D or 2D NDArrays and have certain operations implemented (i.e., eigen and inv).

using cuNumeric
using LinearAlgebra

one_dim = cuNumeric.NDArray([1,2,3,4,5])
two_dim = cuNumeric.rand(5,5)

D1 = Diagonal(one_dim)
D2 = Diagonal(two_dim)

evals, evecs = eigen(D1)
D1_inv = inv(D1)

D1 ./= 2 # stays diagonal
arr = D2 .+ two_dim # densifies because `two_dim` is not guranteed to be diagonal