dolfin team mailing list archive

["Matthew Knepley" <knepley@xxxxxxxxx>]

On Mon, Jul 21, 2008 at 4:35 PM, Anders Logg <logg@xxxxxxxxx> wrote:
> On Mon, Jul 21, 2008 at 04:03:11PM -0500, Matthew Knepley wrote:
>> On Mon, Jul 21, 2008 at 3:55 PM, Matthew Knepley <knepley@xxxxxxxxx> wrote:
>> > On Mon, Jul 21, 2008 at 3:50 PM, Garth N. Wells <gnw20@xxxxxxxxx> wrote:
>> >>
>> >>
>> >> Anders Logg wrote:
>> >>> On Mon, Jul 21, 2008 at 01:48:23PM +0100, Garth N. Wells wrote:
>> >>>>
>> >>>> Anders Logg wrote:
>> >>>>> I have updated the assembly benchmark to include also MTL4, see
>> >>>>>
>> >>>>>    bench/fem/assembly/
>> >>>>>
>> >>>>> Here are the current results:
>> >>>>>
>> >>>>> Assembly benchmark  |  Elasticity3D  PoissonP1  PoissonP2  PoissonP3  THStokes2D  NSEMomentum3D  StabStokes2D
>> >>>>> -------------------------------------------------------------------------------------------------------------
>> >>>>> uBLAS               |        9.0789    0.45645     3.8042     8.0736  14.937         9.2507        3.8455
>> >>>>> PETSc               |        7.7758    0.42798     3.5483     7.3898  13.945         8.1632         3.258
>> >>>>> Epetra              |        8.9516    0.45448     3.7976     8.0679  15.404         9.2341        3.8332
>> >>>>> MTL4                |        8.9729    0.45554     3.7966     8.0759  14.94          9.2568        3.8658
>> >>>>> Assembly            |         7.474    0.43673     3.7341     8.3793  14.633         7.6695        3.3878
>> >>>>>
>> >>
>> >>
>> >> I specified in MTL4Matrix maximum 30 nonzeroes per row, and the results
>> >> change quite a bit,
>> >>
>> >>  Assembly benchmark  |  Elasticity3D  PoissonP1  PoissonP2  PoissonP3
>> >> THStokes2D  NSEMomentum3D  StabStokes2D
>> >>
>> >> -------------------------------------------------------------------------------------------------------------
>> >>  uBLAS               |        7.1881    0.32748     2.7633     5.8311
>> >>     10.968         7.0735        2.8184
>> >>  PETSc               |        5.7868    0.30673     2.5489     5.2344
>> >>     9.8896          6.069        2.3661
>> >>  MTL4                |        2.8641    0.18339     1.6628     2.6811
>> >>     2.8519         3.4843       0.85029
>> >>  Assembly            |        5.5564    0.30896     2.6858     5.9675
>> >>     10.622         5.7144        2.4519
>> >>
>> >>
>> >> MTL4 is a lot faster in all cases.
>>
>> Okay, if you run KSP ex2 (Poisson 2D) and add a logging stage that
>> times assembly (I checked it in to petsc-dev)
>> then 1M unknowns takes about 1s
>>
>>   Matrix Object:
>>     type=seqaij, rows=1000000, cols=1000000
>>     total: nonzeros=4996000, allocated nonzeros=5000000
>>       not using I-node routines
>> Summary of Stages:   ----- Time ------  ----- Flops -----  ---
>> Messages ---  -- Message Lengths --  -- Reductions --
>>                         Avg     %Total     Avg     %Total   counts
>> %Total     Avg         %Total   counts   %Total
>>  0:      Main Stage: 1.4997e+00  56.3%  3.8891e+08 100.0%  0.000e+00
>> 0.0%  0.000e+00        0.0%  2.200e+01  51.2%
>>  1:        Assembly: 1.1648e+00  43.7%  0.0000e+00   0.0%  0.000e+00
>> 0.0%  0.000e+00        0.0%  0.000e+00   0.0%
>>
>> I just cut the solve off. Thus all thos enumber are extemely fishy.
>>
>>   Matt
>
> We shouldn't trust those numbers just yet. Some of it may be Python
> overhead (calling the FFC JIT compiler etc).
>
> Does 1M unknowns mean a unit square divided into 2x1000x1000 right
> triangles?

Its FD Poisson, which gives the same sparsity and values as P1 Poisson, so
its a 1000x1000 quadrilateral grid. This was just to time insertion.

  Matt

> --
> Anders
>
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What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which
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