On May 24, 2012, at 4:10 PM, Barry Smith wrote:
>
> On May 24, 2012, at 2:37 PM, Mark F. Adams wrote:
>
>>
>> On May 24, 2012, at 3:30 PM, Jed Brown wrote:
>>
>>> On Thu, May 24, 2012 at 2:16 PM, Mark F. Adams <mark.adams at columbia.edu>
>>> wrote:
>>> Is Eisenstat really worth it?
>>>
>>> Given a memory centric future and that Jed, even now, is not seeing a win
>>> .. maybe with a regular grid and R/B ordering you can skip a whole pass
>>> through the data but for AIJ (I assume that is what ex5 uses) lexagraphic
>>> ordering is probably a better model and its does not look like a big win to
>>> me.
>>>
>>> Maybe Eisenstat should split the matrix storage similar to the
>>> factorization kernels?
>
> Absolutely.
>>
>> Is it worth adding and maintaining a new kernel for Eisenstat ...
>
> Absolutely. And if it turns out to be too much of a pain to write and
> maintain such a kernel there is something wrong with our programming model
> and code development system. The right system should make all the complexity
> fall away; when the complexity becomes too much of a bear you know you have
> the wrong system.
OK, in that case then I really have to add my parallel Gauss-Siedel to PETSc.
You write the kernels (not hard, just take an IS of rows to process and a flag
to process them in reverse order or not) for AIJ and the BAIJs and I'll convert
my code to C.
Mark
>
> Barry
>
>>
>>>
>>>
>>> Mark
>>>
>>> On May 24, 2012, at 2:48 PM, Barry Smith wrote:
>>>
>>>>
>>>> On May 24, 2012, at 1:20 PM, Jed Brown wrote:
>>>>
>>>>> On Wed, May 23, 2012 at 2:52 PM, Jed Brown <jedbrown at mcs.anl.gov>
>>>>> wrote:
>>>>> On Wed, May 23, 2012 at 2:26 PM, Barry Smith <bsmith at mcs.anl.gov>
>>>>> wrote:
>>>>>
>>>>> Note that you could use -pc_type eisenstat perhaps in this case instead.
>>>>> Might save lots of flops? I've often wondered about doing Mark's
>>>>> favorite chebyshev smoother with Eisenstat, seems like it should be a
>>>>> good match.
>>>>>
>>>>> [0]PETSC ERROR: --------------------- Error Message
>>>>> ------------------------------------
>>>>> [0]PETSC ERROR: No support for this operation for this object type!
>>>>> [0]PETSC ERROR: Cannot have different mat and pmat!
>>>>>
>>>>> Also, I'm having trouble getting Eisenstat to be more than very
>>>>> marginally faster than SOR.
>>>>
>>>> There is still a bug related to Eisenstat. If you are trying to use it
>>>> with kspest you are likely hitting the bug.
>>>>
>>>> I will fix the bug when I have time.
>>>>
>>>> Barry
>>>>
>>>>>
>>>>>
>>>>> I think we should later be getting the eigenvalue estimate by applying
>>>>> the preconditioned operator to a few random vectors, then
>>>>> orthogonalizing. The basic algorithm is to generate a random matrix X
>>>>> (say 5 or 10 columns), compute
>>>>>
>>>>> Y = (P^{-1} A)^q X
>>>>>
>>>>> where q is 1 or 2 or 3, then compute
>>>>>
>>>>> Q R = Y
>>>>>
>>>>> and compute the largest singular value of the small matrix R. The
>>>>> orthogonalization can be done in one reduction and all the MatMults can
>>>>> be done together. Whenever we manage to implement a MatMMult and PCMApply
>>>>> or whatever (names inspired by VecMDot), this will provide a very low
>>>>> communication way to get the eigenvalue estimates.
>>>>>
>>>>>
>>>>> I want to turn off norms in Chebyshev by default (they are very
>>>>> wasteful), but how should I make -mg_levels_ksp_monitor turn them back
>>>>> on? I'm already tired of typing -mg_levels_ksp_norm_type unpreconditioned.
>>>>
>>>>
>>>
>>>
>>
>
>
