Kulkarni [kaushik...@gmail.com]
Sent: Tuesday, April 11, 2017 7:07 AM
To: Dave May
Cc: PETSc users list
Subject: Re: [petsc-users] Solving NON-Diagonally dominant sparse system
But anyway since I am starting off with the exact solution itself, shouldn't
the norm should be zero independent
Nope - welcome to finite precision arithmetic. What's the condition number?
On Tue, 11 Apr 2017 at 14:07, Kaushik Kulkarni wrote:
> But anyway since I am starting off with the exact solution itself,
> shouldn't the norm should be zero independent of the conditioning?
>
>
But anyway since I am starting off with the exact solution itself,
shouldn't the norm should be zero independent of the conditioning?
On Tue, Apr 11, 2017 at 11:57 AM, Dave May wrote:
>
>
> On Tue, 11 Apr 2017 at 07:28, Kaushik Kulkarni
> wrote:
>
On Tue, 11 Apr 2017 at 07:28, Kaushik Kulkarni wrote:
> A strange behavior I am observing is:
> Problem: I have to solve A*x=rhs, and currently I am currently trying to
> solve for a system where I know the exact solution. I have initialized the
> exact solution in the Vec
A strange behavior I am observing is:
Problem: I have to solve A*x=rhs, and currently I am currently trying to
solve for a system where I know the exact solution. I have initialized the
exact solution in the Vec x_exact.
MatMult(A, x_exact, dummy);// Storing the value of A*x_exact in dummy
Thank you for the inputs.
I tried Barry' s suggestion to use SuperLU, but the solution does not
converge and on doing -ksp_monitor -ksp_converged_reason. I get the
following error:-
240 KSP Residual norm 1.722571678777e+07
Linear solve did not converge due to DIVERGED_DTOL iterations 240
For some
If you need to use SuperLU_DIST, the pivoting is done statically, using
maximum weighted matching, so the small diagonals are usually taken care as
well. It is not as good as partial pivoting, but works most of the time.
Sherry
On Mon, Apr 10, 2017 at 12:07 PM, Barry Smith
I would suggest using ./configure --download-superlu and then when running
the program -pc_type lu -pc_factor_mat_solver_package superlu
Note that this is SuperLU, it is not SuperLU_DIST. Superlu uses partial
pivoting for numerical stability so should be able to handle the small or zero