Sorry. What I mean is that, for example, I have a matrix
            [a1, a2, a3]
    mij = [b1, b2, b3] ,
            [c1, c2, c3]
and using 3 cups. Thus, mij in cpu 2 is
    mij_2 = [b1, b2, b3] .

The local index of element b1 is (1, 1) and it's global index is (2, 1).
How can I get the global index from the local index, and local index from
global index?

Thanks.
2016-09-17
Best,
Regards,
Zhang Ji
Beijing Computational Science Research Center
E-mail: got...@gmail.com




Wayne

On Sat, Sep 17, 2016 at 2:24 AM, Barry Smith <bsm...@mcs.anl.gov> wrote:

>
>    "Gives wrong answers" is not very informative. What answer do you
> expect and what answer do you get?
>
>   Note that each process is looping over mSizes?
>
> for i in range(len(mSizes)):
>     for j in range(len(mSizes)):
>
>   Is this what you want? It doesn't seem likely that you want all
> processes to generate all information in the matrix. Each process should be
> doing a subset of the generation.
>
>    Barry
>
> > On Sep 16, 2016, at 11:03 AM, Ji Zhang <got...@gmail.com> wrote:
> >
> > Dear all,
> >
> > I have a number of small 'mpidense' matrices mij, and I want to
> construct them to a big 'mpidense' matrix M like this:
> >      [  m11  m12  m13  ]
> > M =  |  m21  m22  m23  |   ,
> >      [  m31  m32  m33  ]
> >
> > And a short demo is below. I'm using python, but their grammar are
> similar.
> > import numpy as np
> > from petsc4py import PETSc
> > import sys, petsc4py
> >
> >
> > petsc4py.init(sys.argv)
> > mSizes = (2, 2)
> > mij = []
> >
> > # create sub-matrices mij
> > for i in range(len(mSizes)):
> >     for j in range(len(mSizes)):
> >         temp_m = PETSc.Mat().create(comm=PETSc.COMM_WORLD)
> >         temp_m.setSizes(((None, mSizes[i]), (None, mSizes[j])))
> >         temp_m.setType('mpidense')
> >         temp_m.setFromOptions()
> >         temp_m.setUp()
> >         temp_m[:, :] = np.random.random_sample((mSizes[i], mSizes[j]))
> >         temp_m.assemble()
> >         temp_m.view()
> >         mij.append(temp_m)
> >
> > # Now we have four sub-matrices. I would like to construct them into a
> big matrix M.
> > M = PETSc.Mat().create(comm=PETSc.COMM_WORLD)
> > M.setSizes(((None, np.sum(mSizes)), (None, np.sum(mSizes))))
> > M.setType('mpidense')
> > M.setFromOptions()
> > M.setUp()
> > mLocations = np.insert(np.cumsum(mSizes), 0, 0)    # mLocations = [0,
> mSizes]
> > for i in range(len(mSizes)):
> >     for j in range(len(mSizes)):
> >         temp_m = mij[i*len(mSizes)+j].getDenseArray()
> >         for k in range(temp_m.shape[0]):
> >             M.setValues(mLocations[i]+k, np.arange(mLocations[j],
> mLocations[j+1],dtype='int32'), temp_m[k, :])
> > M.assemble()
> > M.view()
> > The code works well in a single cup, but give wrong answer for 2 and
> more cores.
> >
> > Thanks.
> > 2016-09-17
> > Best,
> > Regards,
> > Zhang Ji
> > Beijing Computational Science Research Center
> > E-mail: got...@gmail.com
> >
> >
>
>

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