Hi! I would like to do a matrix-vector multiplication (besides using linear solvers and so on) with petsc4py. I took the matrix from this example (https://bitbucket.org/petsc/petsc4py/src/master/demo/kspsolve/petsc-mat.py) and applied it to a PETSc Vector. All works well in serial, but in parallel (in particular if ordering becomes relevant) the resulting vector looks very different. Using the shell matrix of this example (https://bitbucket.org/petsc/petsc4py/src/master/demo/poisson2d/poisson2d.py) helps, but then I cannot use matrix-based preconditioners for KSP directly (right?). I also tried using DMDA for creating vectors and matrix and for taking care of their ordering (which seems to be my problem here), but that did not help either.
So, my question is this: How do I do easy parallel matrix-vector multiplication with petsc4py in a way that allows me to use parallel linear solvers etc. later on? I want to deal with spatial decomposition as little as possible. What data structures should I use? DMDA or PETSc.Vec() and PETSc.Mat() or something else? Thanks! -Robert- -- Dr. Robert Speck Juelich Supercomputing Centre Institute for Advanced Simulation Forschungszentrum Juelich GmbH 52425 Juelich, Germany Tel: +49 2461 61 1644 Fax: +49 2461 61 6656 Email: r.sp...@fz-juelich.de Website: http://www.fz-juelich.de/ias/jsc/speck_r PinT: http://www.fz-juelich.de/ias/jsc/pint ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------