[petsc-users] A problem with MPI Derived Data Type and 'calloc'

Matthew Knepley knepley at gmail.com
Thu Apr 19 09:35:23 CDT 2012


On Thu, Apr 19, 2012 at 10:18 AM, Zhenglun (Alan) Wei <
zhenglun.wei at gmail.com> wrote:

>   "
>     TESTVAR ***a, ***b, ***c;
>     TESTVAR **aa, **bb, **cc;
>     TESTVAR *arraya, *arrayb, *arrayc;
>
>      arraya = (TESTVAR*) calloc(SIZE*SIZE*SIZE, sizeof(TESTVAR));
>     arrayb = (TESTVAR*) calloc(SIZE*SIZE*SIZE, sizeof(TESTVAR));
>     arrayc = (TESTVAR*) calloc(SIZE*SIZE*SIZE, sizeof(TESTVAR));
>
>      aa =(TESTVAR**) calloc(SIZE*SIZE, sizeof(TESTVAR*));
>     bb =(TESTVAR**) calloc(SIZE*SIZE, sizeof(TESTVAR*));
>     cc =(TESTVAR**) calloc(SIZE*SIZE, sizeof(TESTVAR*));
>
>     for(i = 0; i < SIZE*SIZE; i++) {
>       aa[i] = &arraya[i*SIZE];
>       bb[i] = &arrayb[i*SIZE];
>       cc[i] = &arrayc[i*SIZE];
>     }
>
>      a =(TESTVAR***) calloc(SIZE*SIZE, sizeof(TESTVAR**));
>     b =(TESTVAR***) calloc(SIZE*SIZE, sizeof(TESTVAR**));
>     c =(TESTVAR***) calloc(SIZE*SIZE, sizeof(TESTVAR**));
>
>     for(i = 0; i < SIZE; i++) {
>       a[i] = &aa[i*SIZE];
>       b[i] = &bb[i*SIZE];
>       c[i] = &cc[i*SIZE];
>     }
> "
>   It works. However, I wonder if there is any other good ideas for 3D
> problem other than this kinda of 'two-layer' approach.
>
>  *What is the reason for not using DMDA?
> *In 2D, I established a 2D array for data communication between nodes by
> using MPI derived data type. It allows me to easily communicate both
> contiguous (i.e. MPI_TYPE_CONTIGUOUS) and non-contiguous (i.e.
> MPI_TYPE_VECTOR) data. That is why I use this similar approach in 3D,
> though an additional data type, i.e. MPI_TYPE_INDEXED, need to be used.
> Does DMDA have those type of function or derived data type?
>

It definitely does communication between the local pieces. Do you want
something else?


>  "2, I have a little question on PETSc about 3D processor ordering. Does
>> PETSc have any function giving me the nodes/rank number of neighboring
>> nodes/ranks? Are those 'Application Ordering' functions applicable for my
>> case?"
>>
>
>  *What do you mean by neighboring? If it is jsut stencil neighbors, then
> use a local vector.*
> When I send and receive data with MPI_Send and MPI_RECV, I need provide
> the 'destination' (in MPI_Send refer to'
> http://www.mcs.anl.gov/research/projects/mpi/www/www3/MPI_Send.html') and
> 'source' (in MPI_RECV refer to'
> http://www.mcs.anl.gov/research/projects/mpi/www/www3/MPI_Recv.html'). In
> a 2D problem with Cartesian grid, 4 processes divide the whole domain to 4
> sub-domain.
> ----------------------------
>       2      |      3      |
> ----------------------------
>       0      |      1      |
> ---------------------------
>  Then, for node 1, the neighboring nodes are '0' and '3', which '0' is the
> left node and '3' is the top node. I wonder if PETSc has any function that
> I can call to obtain those neighboring nodes so that I do not need to
> construct my function.
>

Yes, it looks like you should just use a DMDA. See the manual section.

   Matt


> I'm sorry for confusing you.
>
> thanks in advance,
> Alan
>
> On 4/19/2012 4:52 AM, Matthew Knepley wrote:
>
> On Wed, Apr 18, 2012 at 3:52 PM, Alan Wei <zhenglun.wei at gmail.com> wrote:
>
>> Dear all,
>>     I hope you're having a nice day. I have a further question on this
>> issue in 3D.
>> 1, Following the idea of Dr. Brown and Dr. Knepley, I finished a 2D test,
>> which works very fine. Here, I did it in 3D by
>>  "
>>     TESTVAR ***a, ***b, ***c;
>>     TESTVAR **aa, **bb, **cc;
>>     TESTVAR *arraya, *arrayb, *arrayc;
>>
>>      arraya = (TESTVAR*) calloc(SIZE*SIZE*SIZE, sizeof(TESTVAR));
>>     arrayb = (TESTVAR*) calloc(SIZE*SIZE*SIZE, sizeof(TESTVAR));
>>     arrayc = (TESTVAR*) calloc(SIZE*SIZE*SIZE, sizeof(TESTVAR));
>>
>>      aa =(TESTVAR**) calloc(SIZE*SIZE, sizeof(TESTVAR*));
>>     bb =(TESTVAR**) calloc(SIZE*SIZE, sizeof(TESTVAR*));
>>     cc =(TESTVAR**) calloc(SIZE*SIZE, sizeof(TESTVAR*));
>>
>>     for(i = 0; i < SIZE*SIZE; i++) {
>>       aa[i] = &arraya[i*SIZE];
>>       bb[i] = &arrayb[i*SIZE];
>>       cc[i] = &arrayc[i*SIZE];
>>     }
>>
>>      a =(TESTVAR***) calloc(SIZE*SIZE, sizeof(TESTVAR**));
>>     b =(TESTVAR***) calloc(SIZE*SIZE, sizeof(TESTVAR**));
>>     c =(TESTVAR***) calloc(SIZE*SIZE, sizeof(TESTVAR**));
>>
>>     for(i = 0; i < SIZE; i++) {
>>       a[i] = &aa[i*SIZE];
>>       b[i] = &bb[i*SIZE];
>>       c[i] = &cc[i*SIZE];
>>     }
>> "
>>   It works. However, I wonder if there is any other good ideas for 3D
>> problem other than this kinda of 'two-layer' approach.
>>
>
>  What is the reason for not using DMDA?
>
>
>>  2, I have a little question on PETSc about 3D processor ordering. Does
>> PETSc have any function giving me the nodes/rank number of neighboring
>> nodes/ranks? Are those 'Application Ordering' functions applicable for my
>> case?
>>
>
>  What do you mean by neighboring? If it is jsut stencil neighbors, then
> use a local vector.
>
>     Matt
>
>
>>  thanks,
>> Alan
>>
>> On Fri, Apr 13, 2012 at 5:41 PM, Jed Brown <jedbrown at mcs.anl.gov> wrote:
>>
>>>  On Fri, Apr 13, 2012 at 17:38, Zhenglun (Alan) Wei <
>>> zhenglun.wei at gmail.com> wrote:
>>>
>>>>     I have a final question on it. Is it taken a lot of memory for
>>>> doing this? As I understand, pointers won't occupy many memories and it
>>>> works like an alias. It will not, to my limit knowledge, take much extra
>>>> memory by doing this.
>>>
>>>
>>>  A pointer takes about as much space as a floating point value, so that
>>> array of pointers costs about 1*N compared to the N*N matrix.
>>>
>>
>>
>
>
>  --
> 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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