Dear Developers, In short, I need to explicitly use A.solveBackward(b, x) in parallel with petsc4py, where A is a Cholesky factored matrix, but it seems that this is not supported (e.g., for mumps and superlu_dist factorization solver backend). Is it possible to work around this?
In detail, the problem I need to solve is to generate a set of correlated random numbers (denoted by a vector, w) from an uncorrelated one (denoted by a vector n). Denote the covariance matrix of n as C (symmetric). One needs to first factorize C, C = L L^T, and then solve the linear system L^T w = n for w in parallel. Is it possible to reformulate this problem for it to be implemented using petsc4py? Thank you! Yin
