[petsc-users] I am wondering if there is a way to implement SPMM

Hong hzhang at mcs.anl.gov
Thu Aug 6 10:20:42 CDT 2015


Cong:

> Hong,
>
> Sure.
>
> I want to extend the Krylov subspace by step_k dimensions by using
> monomial, which can be defined as
>
> K={Km(1)m Km(2), ..., Km(step_k)}
>   ={Km(1), AKm(1), AKm(2), ... , AKm(step_k-1)}
>   ={R, AR, A^2R, ... A^(step_k-1)R}
>

A subspace with dense matrices as basis?
How large step_k and your matrices will be?

Hong

>
> On Thu, Aug 6, 2015 at 12:23 PM, Hong <hzhang at mcs.anl.gov> wrote:
>
>> Cong,
>>
>> Can you write out math equations for mpk_monomial (),
>> list input and output parameters.
>>
>> Note:
>> 1. MatDuplicate() does not need to be followed by MatAssemblyBegin/End
>> 2. MatMatMult(A,Km(stepIdx-1),MAT_REUSE_MATRIX,..) must be called after
>>     MatMatMult(A,Km(stepIdx-1),MAT_INITIAL_MATRIX,..)
>>
>> Hong
>>
>>
>> On Wed, Aug 5, 2015 at 8:56 PM, Cong Li <solvercorleone at gmail.com> wrote:
>>
>>> The entire source code files are attached.
>>>
>>> Also I copy and paste the here in this email
>>>
>>> thanks
>>>
>>> program test
>>>
>>>   implicit none
>>>
>>> #include <finclude/petscsys.h>
>>> #include <finclude/petscvec.h>
>>> #include <finclude/petscmat.h>
>>> #include <finclude/petscviewer.h>
>>>
>>>
>>>   PetscViewer    :: view
>>>   ! sparse matrix
>>>   Mat            :: A
>>>   ! distributed dense matrix of size n x m
>>>   Mat            :: B, X, R, QDlt, AQDlt
>>>   ! distributed dense matrix of size n x (m x k)
>>>   Mat            :: Q, K, AQ_p, AQ
>>>   ! local dense matrix (every process keep the identical copies), (m x
>>> k) x (m x k)
>>>   Mat            :: AConjPara, QtAQ, QtAQ_p, Dlt
>>>
>>>   PetscInt       :: nDim, mDim, rhsNDim,rhsMDim,ierr, maxIter, iter,
>>> step_k,bsize
>>>   PetscInt       :: ownRowS,ownRowE
>>>   PetscScalar, allocatable :: XInit(:,:)
>>>   PetscInt       :: XInitI, XInitJ
>>>   PetscScalar    :: v=1.0
>>>   PetscBool      :: flg
>>>   PetscMPIInt    :: size, rank
>>>
>>>   character(128) ::  fin, rhsfin
>>>
>>>
>>>   call PetscInitialize(PETSC_NULL_CHARACTER,ierr)
>>>   call MPI_Comm_size(PETSC_COMM_WORLD,size,ierr)
>>>   call MPI_Comm_rank(PETSC_COMM_WORLD,rank,ierr)
>>>
>>>   ! read binary matrix file
>>>   call PetscOptionsGetString(PETSC_NULL_CHARACTER,'-f',fin,flg,ierr)
>>>   call PetscOptionsGetString(PETSC_NULL_CHARACTER,'-r',rhsfin,flg,ierr)
>>>
>>>   call PetscOptionsGetInt(PETSC_NULL_CHARACTER,'-i',maxIter,flg,ierr)
>>>   call PetscOptionsGetInt(PETSC_NULL_CHARACTER,'-k',step_k,flg,ierr)
>>>   call PetscOptionsGetInt(PETSC_NULL_CHARACTER,'-w',bsize,flg,ierr)
>>>
>>>
>>>   call
>>> PetscViewerBinaryOpen(PETSC_COMM_WORLD,fin,FILE_MODE_READ,view,ierr)
>>>   call MatCreate(PETSC_COMM_WORLD,A,ierr)
>>>   call MatSetType(A,MATAIJ,ierr)
>>>   call MatLoad(A,view,ierr)
>>>   call PetscViewerDestroy(view,ierr)
>>>   ! for the time being, assume mDim == nDim is true
>>>   call MatGetSize(A, nDim, mDim, ierr)
>>>
>>>   if (rank == 0) then
>>>     print*,'Mat Size = ', nDim, mDim
>>>   end if
>>>
>>>   call MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatGetOwnershipRange(A,ownRowS,ownRowE, ierr)
>>>
>>>   ! create right-and-side matrix
>>>   ! for the time being, choose row-wise decomposition
>>>   ! for the time being, assume nDim%size = 0
>>>   call MatCreateDense(PETSC_COMM_WORLD, (ownRowE - ownRowS), &
>>>                       bsize, nDim, bsize,PETSC_NULL_SCALAR, B, ierr)
>>>   call
>>> PetscViewerBinaryOpen(PETSC_COMM_WORLD,rhsfin,FILE_MODE_READ,view, ierr)
>>>   call MatLoad(B,view,ierr)
>>>   call PetscViewerDestroy(view,ierr)
>>>   call MatGetSize(B, rhsMDim, rhsNDim, ierr)
>>>   if (rank == 0) then
>>>     print*,'MRHS Size actually are:', rhsMDim, rhsNDim
>>>     print*,'MRHS Size should be:', nDim, bsize
>>>   end if
>>>   call MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   ! inintial value guses X
>>>   allocate(XInit(nDim,bsize))
>>>   do XInitI=1, nDim
>>>     do XInitJ=1, bsize
>>>       XInit(XInitI,XInitJ) = 1.0
>>>     end do
>>>   end do
>>>
>>>   call MatCreateDense(PETSC_COMM_WORLD, (ownRowE - ownRowS), &
>>>                       bsize, nDim, bsize,XInit, X, ierr)
>>>
>>>   call MatAssemblyBegin(X, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (X, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>
>>>   !  B, X, R, QDlt, AQDlt
>>>   call MatDuplicate(B, MAT_DO_NOT_COPY_VALUES, R, ierr)
>>>   call MatAssemblyBegin(R, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (R, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(B, MAT_DO_NOT_COPY_VALUES, QDlt, ierr)
>>>   call MatAssemblyBegin(QDlt, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (QDlt, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(B, MAT_DO_NOT_COPY_VALUES, AQDlt, ierr)
>>>   call MatAssemblyBegin(AQDlt, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (AQDlt, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>> ! Q, K, AQ_p, AQ of size n x (m x k)
>>>   call MatCreateDense(PETSC_COMM_WORLD, (ownRowE - ownRowS), &
>>>                       (bsize*step_k), nDim,
>>> (bsize*step_k),PETSC_NULL_SCALAR, Q, ierr)
>>>   call MatAssemblyBegin(Q, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd(Q, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(Q, MAT_DO_NOT_COPY_VALUES, K, ierr)
>>>   call MatAssemblyBegin(K, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd(K, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(Q, MAT_DO_NOT_COPY_VALUES, AQ_p, ierr)
>>>   call MatAssemblyBegin(AQ_p, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd(AQ_p, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(Q, MAT_DO_NOT_COPY_VALUES, AQ, ierr)
>>>   call MatAssemblyBegin(AQ, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd(AQ, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>> ! QtAQ, QtAQ_p, Dlt of size (m x k) x (m x k)
>>>   call MatCreateSeqDense(PETSC_COMM_SELF,(bsize*step_k),(bsize*step_k),&
>>>                          PETSC_NULL_SCALAR, QtAQ, ierr)
>>>   call MatAssemblyBegin(QtAQ, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (QtAQ, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(QtAQ, MAT_DO_NOT_COPY_VALUES, QtAQ_p    , ierr)
>>>   call MatAssemblyBegin(QtAQ_p, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (QtAQ_p, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(QtAQ, MAT_DO_NOT_COPY_VALUES, Dlt       , ierr)
>>>   call MatAssemblyBegin(Dlt, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (Dlt, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   call MatDuplicate(QtAQ, MAT_DO_NOT_COPY_VALUES, AConjPara , ierr)
>>>   call MatAssemblyBegin(AConjPara, MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (AConjPara, MAT_FINAL_ASSEMBLY, ierr)
>>>
>>> ! calculation for R
>>>
>>> ! call matrix powers kernel
>>>   call mpk_monomial (K, A, R, step_k, rank,size)
>>>
>>> ! destory matrices
>>>   deallocate(XInit)
>>>
>>>   call MatDestroy(B, ierr)
>>>   call MatDestroy(X, ierr)
>>>   call MatDestroy(R, ierr)
>>>   call MatDestroy(QDlt, ierr)
>>>   call MatDestroy(AQDlt, ierr)
>>>   call MatDestroy(Q, ierr)
>>>   call MatDestroy(K, ierr)
>>>   call MatDestroy(AQ_p, ierr)
>>>   call MatDestroy(AQ, ierr)
>>>   call MatDestroy(QtAQ, ierr)
>>>   call MatDestroy(QtAQ_p, ierr)
>>>   call MatDestroy(Dlt, ierr)
>>>
>>>
>>>   call PetscFinalize(ierr)
>>>
>>>   stop
>>>
>>> end program test
>>>
>>>
>>> subroutine mpk_monomial (K, A, R, step_k, rank, sizeMPI)
>>> implicit none
>>>
>>> #include <finclude/petscsys.h>
>>> #include <finclude/petscvec.h>
>>> #include <finclude/petscmat.h>
>>> #include <finclude/petscviewer.h>
>>>
>>> Mat            :: K, Km(step_k)
>>> Mat            :: A, R
>>> PetscMPIInt    :: sizeMPI, rank
>>> PetscInt       :: nDim, bsize, step_k, local_RRow, local_RCol, genIdx
>>> PetscInt       :: ierr
>>> PetscInt       :: stepIdx, blockShift, localRsize
>>>   PetscScalar    :: KArray(1), RArray(1), PetscScalarSize
>>>   PetscOffset    :: KArrayOffset, RArrayOffset
>>>
>>> call MatGetSize(R, nDim, bsize, ierr)
>>>   if (rank == 0) then
>>>    print*,'Mat Size = ', nDim, bsize
>>>   end if
>>>
>>>   call MatGetArray(K,KArray,KArrayOffset,ierr)
>>>
>>>   call MatGetLocalSize(R,local_RRow,local_RCol)
>>> !   print *, "local_RRow,local_RCol", local_RRow,local_RCol
>>>
>>>   ! get arry from R to add values to K(1)
>>>   call MatGetArray(R,RArray,RArrayOffset,ierr)
>>>
>>>   call MatCreateDense(PETSC_COMM_WORLD,  PETSC_DECIDE, &
>>>                         PETSC_DECIDE , nDim, bsize,KArray(KArrayOffset +
>>> 1), Km(1), ierr)
>>>
>>>
>>> !   call PetscMemmove(KArray(KArrayOffset + 1),RArray(RArrayOffset + 1) &
>>> !                  ,local_RRow * local_RCol *
>>> STORAGE_SIZE(PetscScalarSize), ierr)
>>>
>>>   localRsize = local_RRow * local_RCol
>>>   do genIdx= 1, localRsize
>>>     KArray(KArrayOffset + genIdx) = RArray(RArrayOffset + genIdx)
>>>   end do
>>>
>>>
>>>   call MatRestoreArray(R,RArray,RArrayOffset,ierr)
>>>
>>>   call MatAssemblyBegin(Km(1), MAT_FINAL_ASSEMBLY, ierr)
>>>   call MatAssemblyEnd  (Km(1), MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   do stepIdx= 2, step_k
>>>
>>>     blockShift = KArrayOffset + (stepIdx-1) * (local_RRow * local_RCol)
>>>
>>>     call MatCreateDense(PETSC_COMM_WORLD,  PETSC_DECIDE, &
>>>                         PETSC_DECIDE , nDim, bsize,KArray(blockShift+1),
>>> Km(stepIdx), ierr)
>>>     call MatAssemblyBegin(Km(stepIdx), MAT_FINAL_ASSEMBLY, ierr)
>>>     call MatAssemblyEnd  (Km(stepIdx), MAT_FINAL_ASSEMBLY, ierr)
>>>
>>>   end do
>>>
>>>   call MatRestoreArray(K,KArray,KArrayOffset,ierr)
>>>
>>> !   do stepIdx= 2, step_k
>>>   do stepIdx= 2,2
>>>
>>>     call
>>> MatMatMult(A,Km(stepIdx-1),MAT_REUSE_MATRIX,PETSC_DEFAULT_INTEGER,Km(stepIdx),
>>> ierr)
>>> !     call
>>> MatMatMult(A,Km(stepIdx-1),MAT_INITIAL_MATRIX,PETSC_DEFAULT_INTEGER,Km(stepIdx),
>>> ierr)
>>>   end do
>>>
>>> !   call MatView(K,PETSC_VIEWER_STDOUT_WORLD,ierr)
>>>
>>> end subroutine mpk_monomial
>>>
>>>
>>>
>>> Cong Li
>>>
>>> On Thu, Aug 6, 2015 at 3:30 AM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>>>
>>>>
>>>>    Send the entire code so that we can compile it and run it ourselves
>>>> to see what is going wrong.
>>>>
>>>>   Barry
>>>>
>>>> > On Aug 5, 2015, at 4:42 AM, Cong Li <solvercorleone at gmail.com> wrote:
>>>> >
>>>> > Hi
>>>> >
>>>> > I tried the method you suggested. However, I got the error message.
>>>> > My code and message are below.
>>>> >
>>>> > K is the big matrix containing column matrices.
>>>> >
>>>> > code:
>>>> >
>>>> > call MatGetArray(K,KArray,KArrayOffset,ierr)
>>>> >
>>>> > call MatGetLocalSize(R,local_RRow,local_RCol)
>>>> >
>>>> > call MatGetArray(R,RArray,RArrayOffset,ierr)
>>>> >
>>>> > call MatCreateDense(PETSC_COMM_WORLD,  PETSC_DECIDE, &
>>>> >                         PETSC_DECIDE , nDim,
>>>> bsize,KArray(KArrayOffset + 1), Km(1), ierr)
>>>> >
>>>> >   localRsize = local_RRow * local_RCol
>>>> >   do genIdx= 1, localRsize
>>>> >     KArray(KArrayOffset + genIdx) = RArray(RArrayOffset + genIdx)
>>>> >   end do
>>>> >
>>>> >   call MatRestoreArray(R,RArray,RArrayOffset,ierr)
>>>> >
>>>> >   call MatAssemblyBegin(Km(1), MAT_FINAL_ASSEMBLY, ierr)
>>>> >   call MatAssemblyEnd  (Km(1), MAT_FINAL_ASSEMBLY, ierr)
>>>> >
>>>> >   do stepIdx= 2, step_k
>>>> >
>>>> >     blockShift = KArrayOffset + (stepIdx-1) * (local_RRow *
>>>> local_RCol)
>>>> >
>>>> >     call MatCreateDense(PETSC_COMM_WORLD,  PETSC_DECIDE, &
>>>> >                         PETSC_DECIDE , nDim,
>>>> bsize,KArray(blockShift+1), Km(stepIdx), ierr)
>>>> >     call MatAssemblyBegin(Km(stepIdx), MAT_FINAL_ASSEMBLY, ierr)
>>>> >     call MatAssemblyEnd  (Km(stepIdx), MAT_FINAL_ASSEMBLY, ierr)
>>>> >   end do
>>>> >
>>>> >   call MatRestoreArray(K,KArray,KArrayOffset,ierr)
>>>> >
>>>> >    do stepIdx= 2, step_k
>>>> >
>>>> >     call
>>>> MatMatMult(A,Km(stepIdx-1),MAT_REUSE_MATRIX,PETSC_DEFAULT_INTEGER,Km(stepIdx),
>>>> ierr)
>>>> >   end do
>>>> >
>>>> >
>>>> > And I got the error message as below:
>>>> >
>>>> >
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: Caught signal number 11 SEGV: Segmentation Violation,
>>>> probably memory access out of range
>>>> > [0]PETSC ERROR: Try option -start_in_debugger or
>>>> -on_error_attach_debugger
>>>> > [0]PETSC ERROR: or see
>>>> http://www.mcs.anl.gov/petsc/documentation/faq.html#valgrind[0]PETSC
>>>> ERROR: or try http://valgrind.org on GNU/linux and Apple Mac OS X to
>>>> find memory corruption errors
>>>> > [0]PETSC ERROR: configure using --with-debugging=yes, recompile,
>>>> link, and run
>>>> > [0]PETSC ERROR: to get more information on the crash.
>>>> > [0]PETSC ERROR: --------------------- Error Message
>>>> ------------------------------------
>>>> > [0]PETSC ERROR: Signal received!
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: Petsc Release Version 3.3.0, Patch 7, Sat May 11
>>>> 22:15:24 CDT 2013
>>>> > [0]PETSC ERROR: See docs/changes/index.html for recent updates.
>>>> > [0]PETSC ERROR: See docs/faq.html for hints about trouble shooting.
>>>> > [0]PETSC ERROR: See docs/index.html for manual pages.
>>>> > [0]PETSC ERROR: --------------------[1]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [1]PETSC ERROR: Caught signal number 11 SEGV: Segmentation Violation,
>>>> probably memory access out of range
>>>> > ----------------------------------------------------
>>>> > [0]PETSC ERROR: ./kmath.bcbcg on a arch-fuji named p01-024 by a03293
>>>> Wed Aug  5 18:24:40 2015
>>>> > [0]PETSC ERROR: Libraries linked from
>>>> /volume1/home/ra000005/a03293/kmathlibbuild/petsc-3.3-p7/arch-fujitsu-sparc64fx-opt/lib
>>>> > [0]PETSC ERROR: Configure run at Tue Jul 28 19:23:51 2015
>>>> > [0]PETSC ERROR: Configure options --known-level1-dcache-size=32768
>>>> --known-level1-dcache-linesize=32 --known-level1-dcache-assoc=0
>>>> --known-memcmp-ok=1 --known-sizeof-char=1 --known-sizeof-void-p=8
>>>> --known-sizeof-short=2 --known-sizeof-int=4 --known-sizeof-long=8
>>>> --known-sizeof-long-long=8 --known-sizeof-float=4 --known-sizeof-double=8
>>>> --known-sizeof-size_t=8 --known-bits-per-byte=8 --known-sizeof-MPI_Comm=8
>>>> --known-sizeof-MPI_Fint=4 --known-mpi-long-double=1
>>>> --known-mpi-c-double-complex=1 --with-cc=mpifccpx --CFLAGS="-mt -Xg"
>>>> --COPTFLAGS=-Kfast,openmp --with-cxx=mpiFCCpx --CXXFLAGS=-mt
>>>> --CXXOPTFLAGS=-Kfast,openmp --with-fc=mpifrtpx --FFLAGS=-Kthreadsafe
>>>> --FOPTFLAGS=-Kfast,openmp --with-blas-lapack-lib="-SCALAPACK -SSL2"
>>>> --with-x=0 --with-c++-support --with-batch=1 --with-info=1
>>>> --with-debugging=0 --known-mpi-shared-libraries=0 --with-valgrind=0
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: User provided function() line 0 in unknown directory
>>>> unknown file
>>>> >
>>>> --------------------------------------------------------------------------
>>>> > [mpi::mpi-api::mpi-abort]
>>>> > MPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD
>>>> > with errorcode 59.
>>>> >
>>>> > NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.
>>>> > You may or may not see output from other processes, depending on
>>>> > exactly when Open MPI kills them.
>>>> >
>>>> --------------------------------------------------------------------------
>>>> > [p01-024:26516]
>>>> /opt/FJSVtclang/GM-1.2.0-18/lib64/libmpi.so.0(orte_errmgr_base_error_abort+0x84)
>>>> [0xffffffff0091f684]
>>>> > [p01-024:26516]
>>>> /opt/FJSVtclang/GM-1.2.0-18/lib64/libmpi.so.0(ompi_mpi_abort+0x51c)
>>>> [0xffffffff006c389c]
>>>> > [p01-024:26516]
>>>> /opt/FJSVtclang/GM-1.2.0-18/lib64/libmpi.so.0(MPI_Abort+0x6c)
>>>> [0xffffffff006db3ac]
>>>> > [p01-024:26516]
>>>> /opt/FJSVtclang/GM-1.2.0-18/lib64/libtrtmet_c.so.1(MPI_Abort+0x2c)
>>>> [0xffffffff00281bf0]
>>>> > [p01-024:26516] ./kmath.bcbcg [0x1bf620]
>>>> > [p01-024:26516] ./kmath.bcbcg [0x1bf20c]
>>>> > [p01-024:26516] /lib64/libc.so.6(killpg+0x48) [0xffffffff02d52600]
>>>> > [p01-024:26516] [(nil)]
>>>> > [p01-024:26516] ./kmath.bcbcg [0x1a2054]
>>>> > [p01-024:26516] ./kmath.bcbcg [0x1064f8]
>>>> > [p01-024:26516] ./kmath.bcbcg(MAIN__+0x9dc) [0x105d1c]
>>>> > [p01-024:26516] ./kmath.bcbcg(main+0xec) [0x8a329c]
>>>> > [p01-024:26516] /lib64/libc.so.6(__libc_start_main+0x194)
>>>> [0xffffffff02d3b81c]
>>>> > [p01-024:26516] ./kmath.bcbcg [0x1051ec]
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: Caught signal number 15 Terminate: Somet process (or
>>>> the batch system) has told this process to end
>>>> > [0]PETSC ERROR: Try option -start_in_debugger or
>>>> -on_error_attach_debugger
>>>> > [0]PETSC ERROR: or see
>>>> http://www.mcs.anl.gov/petsc/documentation/faq.html#valgrind[0]PETSC
>>>> ERROR: or try http://valgrind.org on GNU/linux and Apple Mac OS X to
>>>> find memory corruption errors
>>>> > [0]PETSC ERROR: configure using --with-debugging=yes, recompile,
>>>> link, and run
>>>> > [0]PETSC ERROR: to get more information on the crash.
>>>> > [0]PETSC ERROR: --------------------- Error Message
>>>> ------------------------------------
>>>> > [0]PETSC ERROR: Signal received!
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: Petsc Release Version 3.3.0, Patch 7, Sat May 11
>>>> 22:15:24 CDT 2013
>>>> > [0]PETSC ERROR: See docs/changes/index.html for recent updates.
>>>> > [0]PETSC ERROR: See docs/faq.html for hints about trouble shooting.
>>>> > [0]PETSC ERROR: See docs/index.html for manual pages.
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: ./kmath.bcbcg on a arch-fuji named p01-024 by a03293
>>>> Wed Aug  5 18:24:40 2015
>>>> > [0]PETSC ERROR: Libraries linked from
>>>> /volume1/home/ra000005/a03293/kmathlibbuild/petsc-3.3-p7/arch-fujitsu-sparc64fx-opt/lib
>>>> > [0]PETSC ERROR: Configure run at Tue Jul 28 19:23:51 2015
>>>> > [0]PETSC ERROR: Configure options --known-level1-dcache-size=32768
>>>> --known-level1-dcache-linesize=32 --known-level1-dcache-assoc=0
>>>> --known-memcmp-ok=1 --known-sizeof-char=1 --known-sizeof-void-p=8
>>>> --known-sizeof-short=2 --known-sizeof-int=4 --known-sizeof-long=8
>>>> --known-sizeof-long-long=8 --known-sizeof-float=4 --known-sizeof-double=8
>>>> --known-sizeof-size_t=8 --known-bits-per-byte=8 --known-sizeof-MPI_Comm=8
>>>> --known-sizeof-MPI_Fint=4 --known-mpi-long-double=1
>>>> --known-mpi-c-double-complex=1 --with-cc=mpifccpx --CFLAGS="-mt -Xg"
>>>> --COPTFLAGS=-Kfast,openmp --with-cxx=mpiFCCpx --CXXFLAGS=-mt
>>>> --CXXOPTFLAGS=-Kfast,openmp --with-fc=mpifrtpx --FFLAGS=-Kthreadsafe
>>>> --FOPTFLAGS=-Kfast,openmp --with-blas-lapack-lib="-SCALAPACK -SSL2"
>>>> --with-x=0 --with-c++-support --with-batch=1 --with-info=1
>>>> --with-debugging=0 --known-mpi-shared-libraries=0 --with-valgrind=0
>>>> > [0]PETSC ERROR:
>>>> ------------------------------------------------------------------------
>>>> > [0]PETSC ERROR: User provided function() line 0 in unknown directory
>>>> unknown file
>>>> > [ERR.] PLE 0019 plexec One of MPI processes was
>>>> aborted.(rank=0)(nid=0x020a0028)(CODE=1938,793745140674134016,15104)
>>>> >
>>>> > However, if I change from
>>>> > call
>>>> MatMatMult(A,Km(stepIdx-1),MAT_REUSE_MATRIX,PETSC_DEFAULT_INTEGER,Km(stepIdx),
>>>> ierr)
>>>> > to
>>>> > call MatMatMult(A,Km(stepIdx-1),
>>>> MAT_INITIAL_MATRIX,PETSC_DEFAULT_INTEGER,Km(stepIdx), ierr)
>>>> >
>>>> > everything is fine.
>>>> >
>>>> > could you please suggest some way to solve this?
>>>> >
>>>> > Thanks
>>>> >
>>>> > Cong Li
>>>> >
>>>> > On Wed, Aug 5, 2015 at 10:53 AM, Cong Li <solvercorleone at gmail.com>
>>>> wrote:
>>>> > Thank you very much for your help and suggestions.
>>>> > With your help, finally I could continue my project.
>>>> >
>>>> > Regards
>>>> >
>>>> > Cong Li
>>>> >
>>>> >
>>>> >
>>>> > On Wed, Aug 5, 2015 at 3:09 AM, Barry Smith <bsmith at mcs.anl.gov>
>>>> wrote:
>>>> >
>>>> >   From the manual page:  Unless scall is MAT_REUSE_MATRIX C will be
>>>> created.
>>>> >
>>>> >   Since you want to use the C that is passed in you should use
>>>> MAT_REUSE_MATRIX.
>>>> >
>>>> >   Note that since your B and C matrices are dense the issue of
>>>> sparsity pattern of C is not relevant.
>>>> >
>>>> >   Barry
>>>> >
>>>> > > On Aug 4, 2015, at 11:59 AM, Cong Li <solvercorleone at gmail.com>
>>>> wrote:
>>>> > >
>>>> > > Thanks very much. This answer is very helpful.
>>>> > > And I have a following question.
>>>> > > If I create B1, B2, .. by the way you suggested and then use
>>>> MatMatMult to do SPMM.
>>>> > > PetscErrorCode  MatMatMult(Mat A,Mat B,MatReuse scall,PetscReal
>>>> fill,Mat *C)
>>>> > > should I use  MAT_REUSE_MATRIX for MatReuse part of the arguement.
>>>> > >
>>>> > > Thanks
>>>> > >
>>>> > > Cong Li
>>>> > >
>>>> > > On Wed, Aug 5, 2015 at 1:27 AM, Barry Smith <bsmith at mcs.anl.gov>
>>>> wrote:
>>>> > >
>>>> > > > On Aug 4, 2015, at 4:09 AM, Cong Li <solvercorleone at gmail.com>
>>>> wrote:
>>>> > > >
>>>> > > > I am sorry that I should have explained it more clearly.
>>>> > > > Actually I want to compute a recurrence.
>>>> > > >
>>>> > > > Like, I want to firstly compute A*X1=B1, and then calculate
>>>> A*B1=B2, A*B2=B3 and so on.
>>>> > > > Finally I want to combine all these results into a bigger matrix
>>>> C=[B1,B2 ...]
>>>> > >
>>>> > >    First create C with MatCreateDense(,&C). Then call
>>>> MatDenseGetArray(C,&array); then create B1 with
>>>> MatCreateDense(....,array,&B1); then create
>>>> > > B2 with MatCreateDense(...,array+shift,&B2) etc where shift equals
>>>> the number of __local__ rows in B1 times the number of columns in B1, then
>>>> create B3 with a larger shift etc.
>>>> > >
>>>> > >    Note that you are "sharing" the array space of C with B1, B2,
>>>> B3, ..., each Bi contains its columns of the C matrix.
>>>> > >
>>>> > >   Barry
>>>> > >
>>>> > >
>>>> > >
>>>> > > >
>>>> > > > Is there any way to do this efficiently.
>>>> > > >
>>>> > > >
>>>> > > >
>>>> > > > On Tue, Aug 4, 2015 at 5:45 PM, Patrick Sanan <
>>>> patrick.sanan at gmail.com> wrote:
>>>> > > > On Tue, Aug 04, 2015 at 03:42:14PM +0900, Cong Li wrote:
>>>> > > > > Thanks for your reply.
>>>> > > > >
>>>> > > > > I have an other question.
>>>> > > > > I want to do SPMM several times and combine result matrices
>>>> into one bigger
>>>> > > > > matrix.
>>>> > > > > for example
>>>> > > > > I firstly calculate AX1=B1, AX2=B2 ...
>>>> > > > > then I want to combine B1, B2.. to get a C, where C=[B1,B2...]
>>>> > > > >
>>>> > > > > Could you please suggest a way of how to do this.
>>>> > > > This is just linear algebra, nothing to do with PETSc
>>>> specifically.
>>>> > > > A * [X1, X2, ... ] = [AX1, AX2, ...]
>>>> > > > >
>>>> > > > > Thanks
>>>> > > > >
>>>> > > > > Cong Li
>>>> > > > >
>>>> > > > > On Tue, Aug 4, 2015 at 3:27 PM, Jed Brown <jed at jedbrown.org>
>>>> wrote:
>>>> > > > >
>>>> > > > > > Cong Li <solvercorleone at gmail.com> writes:
>>>> > > > > >
>>>> > > > > > > Hello,
>>>> > > > > > >
>>>> > > > > > > I am a PhD student using PETsc for my research.
>>>> > > > > > > I am wondering if there is a way to implement SPMM (Sparse
>>>> matrix-matrix
>>>> > > > > > > multiplication) by using PETSc.
>>>> > > > > >
>>>> > > > > >
>>>> > > > > >
>>>> http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Mat/MatMatMult.html
>>>> > > > > >
>>>> > > >
>>>> > >
>>>> > >
>>>> >
>>>> >
>>>> >
>>>>
>>>>
>>>
>>
>
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