AX=B Fortran Petsc Code

[Tim Stitt]

Matthew,

OK...I see what you are saying.

I initially set A a row at a time but for performance reasons I thought 
doing it at once would be better. I overlooked the fact that the logical 
2D matrix input to MatSetValues() is non-zero values only. With 
hindsight I now remember that was the case for each individual row.

Thanks for pointing that out....

Regards.

Matthew Knepley wrote:
> You appear to be setting every value in the sparse matrix. We do not
> throw out 0 values (since sometimes they are necessary for structural
> reasons). Thus you are allocating a ton of times. You need to remove
> the 0 values before calling MatSetValues (and their associated
> column entires as well).
>
>   Matt
>
> On Nov 14, 2007 8:13 AM, Tim Stitt <timothy.stitt at ichec.ie> wrote:
>   
>> Dear PETSc Users/Developers,
>>
>> I have the following sequential Fortran PETSc code that I have been
>> developing (on and off) based on the kind advice given by members of
>> this list, with respect to solving an inverse sparse matrix problem.
>> Essentially, the code reads in a square double complex matrix from
>> external file of size (order x order) and then proceeds to do a
>> MatMatSolve(), where A is the sparse matrix to invert, B is a dense
>> identity matrix and X is the resultant dense matrix....hope that makes
>> sense.
>>
>> My main problem is that the code stalls on the MatSetValues() for the
>> sparse matrix A. With a trivial test matrix of (224 x 224) the program
>> terminates successfully (by successfully I mean all instructions
>> execute...I am not interested in the validity of X right now).
>> Unfortunately, when I move up to a (2352 x 2352) matrix the
>> MatSetValues() routine for matrix A is still in progress after 15
>> minutes on one processor of our AMD Opteron IBM Cluster. I know that
>> people will be screaming "preallocation"...but I have tried to take this
>> into account by running a loop over the rows in A and counting the
>> non-zero values explicitly prior to creation. I then pass this vector
>> into the creation routine for the nnz argument. For the large (2352 x
>> 2352) problem that seems to be taking forever to set...at most there are
>> only 200 elements per row that are non-zero according to the counts.
>>
>> Can anyone explain why the MatSetValues() routine is taking such a long
>> time. Maybe this expected for this specific task...although it seems
>> very long?
>>
>> I did notice that on the trivial (224 x 224) run that I was still
>> getting mallocs (approx 2000) for the A assembly when I used the -info
>> command line parameter. I thought that it should be 0 if my
>> preallocation counts were exact? Does this hint that I am doing
>> something wrong. I have checked the code but don't see any obvious
>> problems in the logic...not that means anything.
>>
>> I would be grateful if someone could advise on this matter. Also, if you
>> have a few seconds to spare I would be grateful if some experts could
>> scan the remaining logic of the code (not in fine detail)  to make sure
>> that I am doing all that I need to do to get this calculation
>> working...assuming I can resolve the MatSetValues() problem.
>>
>> Once again many thanks in advance,
>>
>> Tim.
>>
>>  ! Initialise the PETSc MPI Harness
>>   call PetscInitialize(PETSC_NULL_CHARACTER,error);CHKERRQ(error)
>>
>>   call MPI_COMM_SIZE(PETSC_COMM_SELF,processes,error);CHKERRQ(error)
>>   call MPI_COMM_RANK(PETSC_COMM_SELF,ID,error);CHKERRQ(error)
>>
>>   ! Read in Matrix
>>   open(321,file='Hamiltonian.bin',form='unformatted')
>>   read(321) order
>>   if (ID==0) then
>>      print *
>>      print *,processes," Processing Elements being used"
>>      print *
>>      print *,"Matrix has order ",order," rows by ",order," columns"
>>      print *
>>   end if
>>
>>   allocate(matrix(order,order))
>>   read(321) matrix
>>   close(321)
>>
>>   ! Allocate array for nnz
>>   allocate(numberZero(order))
>>
>>   ! Count number of non-zero elements in each matrix row
>>   do row=1,order
>>      count=0
>>      do column=1,order
>>         if (matrix(row,column).ne.(0,0)) count=count+1
>>      end do
>>      numberZero(row)=count
>>   end do
>>
>>   ! Declare a PETSc Matrices
>>
>>   call
>> MatCreateSeqAIJ(PETSC_COMM_SELF,order,order,PETSC_NULL_INTEGER,numberZero,A,error);CHKERRQ(error)
>>   call
>> MatCreateSeqAIJ(PETSC_COMM_SELF,order,order,0,PETSC_NULL_INTEGER,factorMat,error);CHKERRQ(error)
>>   call
>> MatCreateSeqDense(PETSC_COMM_SELF,order,order,PETSC_NULL_SCALAR,X,error);CHKERRQ(error)
>>   call
>> MatCreateSeqDense(PETSC_COMM_SELF,order,order,PETSC_NULL_SCALAR,B,error);CHKERRQ(error)
>>
>>   ! Set up zero-based array indexing for use in MatSetValues
>>   allocate(columnIndices(order))
>>
>>   do column=1,order
>>      columnIndices(column)=column-1
>>   end do
>>
>>   ! Need to transpose values array as row-major arrays are used.
>>   call
>> MatSetValues(A,order,columnIndices,order,columnIndices,transpose(matrix),INSERT_VALUES,error);CHKERRQ(error)
>>
>>   ! Assemble Matrix A
>>   call MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error)
>>   call MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error)
>>
>>   deallocate(matrix)
>>
>>   ! Create Index Sets for Factorisation
>>   call
>> ISCreateGeneral(PETSC_COMM_SELF,order,columnIndices,indexSet,error);CHKERRQ(error)
>>   call MatFactorInfoInitialize(info,error);CHKERRQ(error)
>>   call ISSetPermutation(indexSet,error);CHKERRQ(error)
>>   call
>> MatLUFactorSymbolic(A,indexSet,indexSet,info,factorMat,error);CHKERRQ(error)
>>   call MatLUFactorNumeric(A,info,factorMat,error);CHKERRQ(error)
>>
>>   ! A no-longer needed
>>   call MatDestroy(A,error);CHKERRQ(error)
>>
>>   one=(1,0)
>>
>>   ! Set Diagonal elements in Identity Matrix B
>>   do row=0,order-1
>>      call MatSetValue(B,row,row,one,INSERT_VALUES,error);CHKERRQ(error)
>>   end do
>>
>>   ! Assemble B
>>   call MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error)
>>   call MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error)
>>
>>   ! Assemble X
>>   call MatAssemblyBegin(X,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error)
>>   call MatAssemblyEnd(X,MAT_FINAL_ASSEMBLY,error);CHKERRQ(error)
>>
>>   ! Solve AX=B
>>   call MatMatSolve(factorMat,B,X,error);CHKERRQ(error)
>>
>>   ! Deallocate Storage
>>   deallocate(columnIndices)
>>
>>   call MatDestroy(factorMat,error);CHKERRQ(error)
>>   call MatDestroy(B,error);CHKERRQ(error)
>>   call MatDestroy(X,error);CHKERRQ(error)
>>
>>   call PetscFinalize(error)
>>
>> --
>> Dr. Timothy Stitt <timothy_dot_stitt_at_ichec.ie>
>> HPC Application Consultant - ICHEC (www.ichec.ie)
>>
>> Dublin Institute for Advanced Studies
>> 5 Merrion Square - Dublin 2 - Ireland
>>
>> +353-1-6621333 (tel) / +353-1-6621477 (fax)
>>
>>
>>     
>
>
>
>   


-- 
Dr. Timothy Stitt <timothy_dot_stitt_at_ichec.ie>
HPC Application Consultant - ICHEC (www.ichec.ie)

Dublin Institute for Advanced Studies
5 Merrion Square - Dublin 2 - Ireland

+353-1-6621333 (tel) / +353-1-6621477 (fax)