Re: [petsc-users] Parallel vector layout for TAO optimization with separable state/design structure

For a bit of assistance, you can use DMComposite and DMRedundantCreate; see src/snes/tutorials/ex21.c and ex22.c. Note that when computing redundantly, it's critical that the computation be deterministic (i.e., not using atomics or randomness without matching seeds) so the logic stays

Re: [petsc-users] Parallel vector layout for TAO optimization with separable state/design structure

This is a problem with MPI programming and optimization; I am unaware of a perfect solution. Put the design variables into the solution vector on MPI rank 0, and when doing your objective/gradient, send the values to all the MPI processes where you use them. You can use a VecScatter to

[petsc-users] Parallel vector layout for TAO optimization with separable state/design structure

Hi Petsc team, I have a question regarding parallel layout of a Petsc vector to be used in TAO optimizers for cases where the optimization variables split into ‘design’ and ‘state’ variables (e.g. such as in PDE-constrained optimization as in tao_lcl). In our case, the state variable naturally