some sor questions

[Barry Smith]

   I have pushed the support, so when possible the first Richardson  
iteration will take advantage of the fact that it has a zero initial  
guess.
Please let me know if you have difficulties. Note the convergence  
residuals will be slightly different because the computation of the  
smoother is slightly different when the guess is zero. Both answers  
are equally "correct".

    Barry

On Sep 22, 2009, at 3:37 PM, Stephan Kramer wrote:

> Thanks for your answers
>
> Barry Smith wrote:
>> On Sep 22, 2009, at 8:47 AM, Stephan Kramer wrote:
>>> Hi all,
>>>
>>> I have some questions basically about the MatRelax_SeqAIJ routine:
>>>
>>> If I understand correctly there are 2 versions of the sor routine   
>>> depending on whether or not there is a zero guess, so that with a   
>>> zero guess in the forward sweep you don't need to multiply the  
>>> upper  diagonal part U with the part of the x vector that is still  
>>> zero.  Why then does it look like that both versions log the same  
>>> number of  flops? I would have expected that the full forward  
>>> sweep (i.e. no  zero guess) takes 2*a->nz flops (i.e. the same as  
>>> a matvec) and not  a->nz.
>>    You are right. This is an error in our code. It will be in the   
>> next patch.
>>> Why does the Richardson iteration with sor not take the zero  
>>> guess  into account, i.e. why does PCApplyRichardson_SOR not set   
>>> SOR_ZERO_INIT_GUESS in the call to MatRelax if the Richardson ksp   
>>> has a zero initial guess set?
>>    This appears to be a design limitation. There is no mechanism  
>> to  pass the information that the initial guess is zero into   
>> PCApplyRichardson(). We could add support for this by adding one  
>> more  argument to PCApplyRichardson() for this information. I don't  
>> see a  simpler way.  If one is running, say 2 iterations of  
>> Richardson then  this would be a measurable improvement in time. If  
>> one is running many  iterations then the savings is tiny. Perhaps  
>> this support should be  added.
>
> I'm thinking of the application of ksp richardson with sor as a  
> smoother in pcmg. In which case the down smoother will have zero  
> initial guess (as it only acts on the residual), and there will be  
> typicaly only 1 or 2 iterations, so the saving would be significant.  
> Is there another way I should set this up instead?
>
>>> In parallel if you specify SOR_LOCAL_FORWARD_SWEEP or   
>>> SOR_LOCAL_BACKWARD_SWEEP it
>>> calls MatRelax on the local part of the matrix, mat->A, with   
>>> its=lits and lits=PETSC_NULL (?).
>>> However the first line of MatRelax_SeqAIJ then says: its =  
>>> its*lits.  Is that right?
>>    This is all wrong. It should be passing 1 in, not PETSC_NULL.  
>> This  was fixed in petsc-dev but not in petsc-3.0.0 I will fix it  
>> in  petsc-3.0.0 and it will be in the next patch.
>>    Thanks for pointing out the problems.
>>    If you plan to use SOR a lot, you might consider switching to   
>> petsc-dev since I have made some improvements there. Also consider  
>> the  Eisenstat trick preconditioner.
>>    Barry
>>> Please tell me if I'm totally misunderstanding how the routine   
>>> works, thanks for any help.
>>>
>>> Cheers
>>> Stephan
>>>
>>> -- 
>>> Stephan Kramer  <s.kramer at imperial.ac.uk>
>>> Applied Modelling and Computation Group,
>>> Department of Earth Science and Engineering,
>>> Imperial College London
>