In the PETSc git branch barry/feature-baij-blockdiagonal-scale I have done the "heavy lifting" for what you need. See https://bitbucket.org/petsc/petsc/branch/barry/feature-baij-blockdiagonal-scale
It scales the Seq BAIJ matrix by its block diagonal. You will need to write a routine to also scale the right hand side vector by the block diagonal and then you can try the preconditioner for sequential code. Write something like VecBlockDiagonalScale(Vec,const PetscScalar *). You get the block size from the vector. Later you or I can add the parallel version (not much more difficult). I don't have time to work on it now. Let us know if you have any difficulties. Barry > On Feb 14, 2018, at 9:10 AM, Xiangdong <[email protected]> wrote: > > The idea goes back to the alternate-block-factorization (ABF) method > > https://link.springer.com/article/10.1007/BF01932753 > > and is widely used in the reservoir simulation, where the unknowns are > pressure and saturation. Although the coupled equations are parabolic, the > pressure equations/variables are more elliptic and the saturation equations > are more hyperbolic. People always decouple the transformed linear equation > to obtain a better (more elliptical) pressure matrix and then apply the AMG > preconditioner on the decoupled matrix. > > https://link.springer.com/article/10.1007/s00791-016-0273-3 > > Thanks. > > Xiangdong > > On Wed, Feb 14, 2018 at 9:49 AM, Smith, Barry F. <[email protected]> wrote: > > Hmm, I never had this idea presented to me, I have no way to know if it is > particularly good or bad. So essentially you transform the matrix "decoupling > the physics alone the diagonal" and then do PCFIELDSPLIT instead of using > PCFIELDSPLIT directly on the original equations. > > Maybe in the long run this should be an option to PCFIEDLSPLIT. In general > we like the solvers to manage any transformations, not require > transformations before calling the solvers. I have to think about this. > > Barry > > > > On Feb 14, 2018, at 8:29 AM, Xiangdong <[email protected]> wrote: > > > > The reason for the operation invdiag(A)*A is to have a decoupled > > matrix/physics for preconditioning. For example, after the transformation, > > the diagonal block is identity matrix ( e.g. [1,0,0;0,1,0;0,0,1] for > > bs=3). One can extract a submatrix (e.g. corresponding to only first > > unknown) and apply special preconditioners for the extracted/decoupled > > matrix. The motivation is that after the transformation, one can get a > > better decoupled matrix to preserve the properties of the unknowns. > > > > Thanks. > > > > Xiangdong > > > > On Tue, Feb 13, 2018 at 6:27 PM, Smith, Barry F. <[email protected]> wrote: > > > > In general you probably don't want to do this. Most good preconditioners > > (like AMG) rely on the matrix having the "natural" scaling that arises from > > the discretization and doing a scaling like you describe destroys that > > natural scaling. You can use PCPBJACOBI to use point block Jacobi > > preconditioner on the matrix without needing to do the scaling up front. > > The ILU preconditioners for BAIJ matrices work directly with the block > > structure so again pre-scaling the matrix buys you nothing. PETSc doesn't > > have any particularly efficient routines for computing what you desire, the > > only way to get something truly efficient is to write the code directly > > using the BAIJ data structure, doable but probably not worth it. > > > > Barry > > > > > > > On Feb 13, 2018, at 5:21 PM, Xiangdong <[email protected]> wrote: > > > > > > Hello everyone, > > > > > > I have a block sparse matrices A created from the DMDA3d. Before passing > > > the matrix to ksp solver, I want to apply a transformation to this > > > matrix: namely A:= invdiag(A)*A. Here invdiag(A) is the inverse of the > > > block diagonal of A. What is the best way to get the transformed matrix? > > > > > > At this moment, I created a new mat IDA=inv(diag(A)) by looping through > > > each row and call MatMatMult to get B=invdiag(A)*A, then destroy the > > > temporary matrix B. However, I prefer the in-place transformation if > > > possible, namely, without the additional matrix B for memory saving > > > purpose. > > > > > > Do you have any suggestion on compute invdiag(A)*A for mpibaij matrix? > > > > > > Thanks for your help. > > > > > > Best, > > > Xiangdong > > > > > > > > > > > > > > > > > >
