[petsc-users] Why use MATMPIBAIJ?

Justin Chang jychang48 at gmail.com
Thu Jan 14 00:13:31 CST 2016


Okay that makes sense, thanks

On Wed, Jan 13, 2016 at 10:12 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:

>
> > On Jan 13, 2016, at 10:24 PM, Justin Chang <jychang48 at gmail.com> wrote:
> >
> > Thanks Barry,
> >
> > 1) So for block matrices, the ja array is smaller. But what's the
> "hardware" explanation for this performance improvement? Does it have to do
> with spatial locality where you are more likely to reuse data in that ja
> array, or does it have to do with the fact that loading/storing smaller
> arrays are less likely to invoke a cache miss, thus reducing the amount of
> bandwidth?
>
> There are two distinct reasons for the improvement:
>
> 1) For 5 by 5 blocks the ja array is 1/25th the size. The "hardware"
> savings is that you have to load something that is much smaller than
> before. Cache/spatial locality have nothing to do with this particular
> improvement.
>
> 2) The other improvement comes from the reuse of each x[j] value
> multiplied by 5 values (a column) of the little block. The hardware
> explanation is that x[j] can be reused in a register for the 5 multiplies
> (while otherwise it would have to come from cache to register 5 times and
> sometimes might even have been flushed from the cache so would have to come
> from memory). This is why we have code like
>
>     for (j=0; j<n; j++) {
>       xb    = x + 5*(*idx++);
>       x1    = xb[0]; x2 = xb[1]; x3 = xb[2]; x4 = xb[3]; x5 = xb[4];
>       sum1 += v[0]*x1 + v[5]*x2 + v[10]*x3  + v[15]*x4 + v[20]*x5;
>       sum2 += v[1]*x1 + v[6]*x2 + v[11]*x3  + v[16]*x4 + v[21]*x5;
>       sum3 += v[2]*x1 + v[7]*x2 + v[12]*x3  + v[17]*x4 + v[22]*x5;
>       sum4 += v[3]*x1 + v[8]*x2 + v[13]*x3  + v[18]*x4 + v[23]*x5;
>       sum5 += v[4]*x1 + v[9]*x2 + v[14]*x3  + v[19]*x4 + v[24]*x5;
>       v    += 25;
>     }
>
> to do the block multiple.
>
> >
> > 2) So if one wants to assemble a monolithic matrix (i.e., aggregation of
> more than one dof per point) then using the BAIJ format is highly
> advisable. But if I want to form a nested matrix, say I am solving Stokes
> equation, then each "submatrix" is of AIJ format? Can these sub matrices
> also be BAIJ?
>
>    Sure, but if you have separated all the variables of pressure,
> velocity_x, velocity_y, etc into there own regions of the vector then the
> block size for the sub matrices would be 1 so BAIJ does not help.
>
>    There are Stokes solvers that use Vanka smoothing that keep the
> variables interlaced and hence would use BAIJ and NOT use fieldsplit
>
>
> >
> > Thanks,
> > Justin
> >
> > On Wed, Jan 13, 2016 at 9:12 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
> >
> > > On Jan 13, 2016, at 9:57 PM, Justin Chang <jychang48 at gmail.com> wrote:
> > >
> > > Hi all,
> > >
> > > 1) I am guessing MATMPIBAIJ could theoretically have better
> performance than simply using MATMPIAIJ. Why is that? Is it similar to the
> reasoning that block (dense) matrix-vector multiply is "faster" than simple
> matrix-vector?
> >
> >   See for example table 1 in
> http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.38.7668&rep=rep1&type=pdf
> >
> > >
> > > 2) I am looking through the manual and online documentation and it
> seems the term "block" used everywhere. In the section on "block matrices"
> (3.1.3 of the manual), it refers to field splitting, where you could either
> have a monolithic matrix or a nested matrix. Does that concept have
> anything to do with MATMPIBAIJ?
> >
> >    Unfortunately the numerical analysis literature uses the term block
> in multiple ways. For small blocks, sometimes called "point-block" with
> BAIJ and for very large blocks (where the blocks are sparse themselves). I
> used fieldsplit for big sparse blocks to try to avoid confusion in PETSc.
> > >
> > > It makes sense to me that one could create a BAIJ where if you have 5
> dofs of the same type of physics (e.g., five different primary species of a
> geochemical reaction) per grid point, you could create a block size of 5.
> And if you have different physics (e.g., velocity and pressure) you would
> ideally want to separate them out (i.e., nested matrices) for better
> preconditioning.
> >
> >    Sometimes you put them together with BAIJ and sometimes you keep them
> separate with nested matrices.
> >
> > >
> > > Thanks,
> > > Justin
> >
> >
>
>
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