dolfin team mailing list archive

[Anders Logg <logg@xxxxxxxxx>]

On Wed, Aug 06, 2008 at 04:24:36AM -0500, Matthew Knepley wrote:
> ---------- Forwarded message ----------
> From: Matthew Knepley <knepley@xxxxxxxxx>
> Date: Wed, Aug 6, 2008 at 4:24 AM
> Subject: Re: [DOLFIN-dev] Assembly benchmark
> To: "Garth N. Wells" <gnw20@xxxxxxxxx>
> 
> 
> On Wed, Aug 6, 2008 at 4:20 AM, Garth N. Wells <gnw20@xxxxxxxxx> wrote:
> >> ok, here's the page, let's see some numbers:
> >>
> >>   http://www.fenics.org/wiki/Benchmark
> >>
> >
> > I just added my results.
> >
> > The most obvious difference in our systems is 32/64 bit which could
> > likely account for the differences. MTL4 seems considerably faster on
> > the 32 bit system.
> 
> I need to understand the categories into which the time is divided:
> 
>  1) They do not add to the total (or even close)

There are 8 tables:

 0 Assemble total
 1 Init dof map
 2 Build sparsity
 3 Init tensor
 4 Delete sparsity
 5 Assemble cells
 6 Overhead

 7 Reassemble total

The first is the total and includes 1-6 so tables 1-6 should
add up to table 0. In fact, table 6 ("Overhead") is computed as the
difference of table 0 and tables 1-5.

Then table 7 reports the total for reassembling into a matrix which
has already been initialized with the correct sparsity pattern (and
used before).

Maybe there's a better way to order/present the tables to make this
clear?

>  2) I am not sure what is going on within each unit

 1 Init dof map

This one does some initialization for computing the dof map. The only
thing that may happen here (for FFC forms) is that we may generate
the edges and faces if those are needed. You can see the difference
for P1, P2 and P3.

 2 Build sparsity

This one computes the sparsity pattern by iterating over all cells,
computing the local-to-global mapping on each cell and counting the
number of nonzeros.

 3 Init tensor

This one initializes the matrix from the sparsity pattern by looking
at the number of nonzeros per row (calling MatSeqAIJSetPreallocation)
in PETSc.

 4 Delete sparsity

This one deletes the sparsity pattern. This shouldn't take any time
but we found in some tests it actually does (due to some STL
peculiarities).

 5 Assemble cells

This one does the actual assembly loop over cells and inserts
(MatSetValues in PETSc).

 6. Overhead

Everything else not specifically accounted for.

>  3) This is still much more expensive than my PETSc example (which can be
>      easily run. Its ex2 in KSP).

Do we use the same mesh? In 2D it's a 256x256 unit square and in 3D
it's a 32x32x32 unit cube.

> Thus it is hard for me to be convinced that something underneath is just not
> preventing fast operation. Furthermore, this is not checked against a
> performance
> model, say plotted against the number of cells.

I agree that would be good to have as well, but there's also a point
in keeping the benchmark small (so it's fast to run and compare).

-- 
Anders

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