After running my simulation multiple times on a multiprocessor computer I've
just verified that using iterative solver (default gmres) in PETSc to solve a
linear system of equations ( Cx=b) with more than 2 processors setting ALWAYS
lead to erroneous result. Running identical code with identical setting except
for the number of processors ( set this to 2) ALWAYS gives me correct result .
I am really not sure what is the point behind including iterative solvers if
they result into erroneous result on a multiprocessor computer. The result I
get from multiprocessor computer is a complete garbage, so I am really not
talking about small percentage of error here. Also, if somebody could
enlighten why the iterative solvers are error prone on multiprocessors that
will be highly appreciated.
I am very hopeful that there is a way around to this problem, because PETSc is
such a powerful and useful library that I really do not want to give up on this
and start something else from scratch.
Would you think that a DIRECT SOLVER would circumvent this problem? My problem
is that I have a very large system of equations and the size of a sparse
coefficient matrix is huge ( > 1e+8). I assemble this matrix in MATLAB, write
to a binary file, and read it in PETSc. So I really need to be able to solve
this system of equations in a cluster of computers (which inherently has
multiprocessors and distributed memory setting). Does this mean I am completely
out of luck with PETSc's iterative solver package and the only hope for me is
the direct solver? I do have MUMPS downloaded and compiled with PETSc, so I
will give that a try and see what results I obtain, but I am really surprised
that iterative solvers are no good in a large multiprocessor settings.
Any insights, suggestions/advice will be highly appreciated.
Thanks.
PS (I can attach my entire code, plots that compare the results obtained by
solving Cx=b in 2 processors vs 12 or 6 processors if any body wants to take a
look at it. I get garbage if I run iterative solver on 12 processors)
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