MatGetLocalSize() and MatDenseGetLocalMatrix()

Matthew Knepley knepley at gmail.com
Tue Jan 6 13:45:05 CST 2009


On Tue, Jan 6, 2009 at 1:43 PM, Yujie <recrusader at gmail.com> wrote:

> Dear Matthew:
>
> Two processors are used. The matrix dimension is 105*108;
>
> MatGetOwnershipRange()
>
> proc1: 0->56
>
> proc2: 56->105
>
> Mat->camp.rstart; Mat->cmap.rend
>
> proc1: 0->54
>
> proc2: 54->108
>
> MatGetLocalSize()
>
> proc1: row 56 col 54
>
> porc2: row 49 col 54
>
> MatDenseGetLocalMatrix()
>
> proc1: 56*108
>
> proc2: 49*108
>
>
Since PETSc matrices are all stored row-wise, even if columns are assigned
to one process
for the other, the storage is divided by row. This GetLocalMatrix() returns
all the rows
associated with a given process.

   Matt


> thanks.
>
> Yujie
>
> On Tue, Jan 6, 2009 at 11:33 AM, Matthew Knepley <knepley at gmail.com>wrote:
>
>> On Tue, Jan 6, 2009 at 11:52 AM, Yujie <recrusader at gmail.com> wrote:
>>
>>> Dear PETSc developers:
>>>
>>> I am trying to use MatGetArray() and MatSetValues() to combine several
>>> MPIDense matrices into one matrix. At the beginning, I use
>>>
>>> MatGetOwnershipRange() and Mat->camp.rstart; Mat->cmap.rend (2.3.3-p8
>>> version) to get the start, end row and column. I can calculate the local
>>> rows and columns.
>>>
>>> I also use MatGetLocalSize() to confirm the accuracy. However, I always
>>> find some data loses in the combined matrix.
>>>
>>> And then, I try to use MatDenseGetLocalMatrix() to get the lcoal matrix
>>> and output it. I find column information by MatGetLocalSize() is not
>>> consistent with by MatDenseGetLocalMatrix(), is it bug? could you give me
>>> some advice? thanks a lot.
>>>
>> What information?
>>
>>   Matt
>>
>>
>>> Regards,
>>>
>>> Yujie
>>>
>> --
>> What most experimenters take for granted before they begin their
>> experiments is infinitely more interesting than any results to which their
>> experiments lead.
>> -- Norbert Wiener
>>
>
>


-- 
What most experimenters take for granted before they begin their experiments
is infinitely more interesting than any results to which their experiments
lead.
-- Norbert Wiener
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