**-ksp_richardson_scale ** -damping factor on the correction (defaults to 1.0)

### Notes

x^{n+1} = x^{n} + scale*B(b - A x^{n})
Here B is the application of the preconditioner

This method often (usually) will not converge unless scale is very small.

### Notes

For some preconditioners, currently SOR, the convergence test is skipped to improve speed,
thus it always iterates the maximum number of iterations you've selected. When -ksp_monitor
(or any other monitor) is turned on, the norm is computed at each iteration and so the convergence test is run unless
you specifically call KSPSetNormType(ksp,KSP_NORM_NONE);
For some preconditioners, currently PCMG and PCHYPRE with BoomerAMG if -ksp_monitor (and also
any other monitor) is not turned on then the convergence test is done by the preconditioner itself and
so the solver may run more or fewer iterations then if -ksp_monitor is selected.

Supports only left preconditioning

If using direct solvers such as PCLU and PCCHOLESKY one generally uses KSPPREONLY which uses exactly one iteration

-ksp_type richardson -pc_type jacobi gives one classically Jacobi preconditioning

### References