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[Joachim Haga <jobh+launchpad@xxxxxxxxx>]

The problem was that multiplication of BC'd matrices leads to all-zero
rows in the result. With newer Trilinos, these are not present in the
sparsity pattern -- and ML doesn't like that at all. (A zero row with
the diagonal present is handled fine though, it's just ignored.) I've
worked around it by doing a preliminary matrix multiplication with dummy
matrices, just to build a full sparsity pattern. Inefficient, but works.

** Changed in: cbc.block
   Importance: Undecided => High

** Changed in: cbc.block
       Status: New => Fix Committed

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https://bugs.launchpad.net/bugs/1063737

Title:
  Crash with explicit matrix multiplies in trilinos

Status in Block operators and algebra for DOLFIN:
  Fix Committed

Bug description:
  Code such as

  M = collapse(C*B)
  prec = ML(M)

  crashes with a memory access error.

  It seems like EpetraExt.Multiply returns a malformed Epetra matrix
  when B and C are rectangular matrices, which then ML chokes on. This
  used to work with older Trilinos releases.

  I will investigate further as time allows, but for now let's call it a
  known problem.

  Example code: demo/navierstokes.py

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