[petsc-users] Sparse matrix partitioning in PETSc

[Junchao Zhang]

>From PETSc FAQ, I learned to convert an ASCII matrix to binary
sequentially, then read in PETSc in parallel
Yes, I want to benchmark parallel SpMV on clusters, in various
implementations, such as PETSc MatMult().
I'm not sure whether I should reorder a matrix before benchmarking. From
the view of benchmarking, maybe I should also benchmark *bad *matrices.

On Sat, Jan 14, 2012 at 12:46 PM, Jed Brown <jedbrown at mcs.anl.gov> wrote:

> On Sat, Jan 14, 2012 at 13:32, Junchao Zhang <junchao.zhang at gmail.com>wrote:
>
>> My matrices are from Florida matrix collection.
>>
>
> These ASCII formats cannot be read efficiently in parallel.
>
>
>>  I want to use them to test MatMult()
>>
>
> You just want to benchmark sparse matrix kernels?
>
> Some might consider it to be cheating, but you should consider also
> reordering the matrices using
> MatGetOrdering(mat,MATORDERINGRCM,&rperm,&cperm). This will tend to improve
> cache reuse and can offer a large (e.g. 2x depending on the matrix) speedup
> relative to the original ordering.
>



-- 
Junchao Zhang
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