dolfin team mailing list archive

[Anders Logg <logg@xxxxxxxxx>]

On Wed, Jul 16, 2008 at 09:48:16PM +0100, Garth N. Wells wrote:
> 
> 
> Anders Logg wrote:
> > Very nice!
> > 
> > Some comments:
> > 
> > 1. Beating uBLAS by a factor 3 is not that hard. 
> 
> A factor 3 is quite something if the matrix is in compressed row format. 
>   DOLFIN assembly times into uBLAS, PETSc and Trilinos matrices are all 
> very close to each other.
> 
> Didem Unat (PhD
> > student at UCSD/Simula) and Ilmar have been looking at the assembly in
> > DOLFIN recently. We've done some initial benchmarks and have started
> > investigating how to speedup the assembly. Take a look at what happens
> > when we assemble into uBLAS:
> > 
> >   (i)   Compute sparsity pattern
> >   (ii)  Reset tensor
> >   (iii) Assemble
> > 
> > For uBLAS, each of these steps is approximately an assembly process.
> > I don't remember the exact numbers, but by just using an
> > std::vector<std::map<int, double> > instead of a uBLAS matrix, one may
> > skip (i) and (ii) and get a speedup.
> >
> 
> You can do this with uBLAS too by using the uBLAS mapped_matrix (uses 
> std::map internally) instead of compressed_matrix. The problem is that 
> it is dead slow for matrix-vector multiplications. Most uBLAS sparse 
> matrix types are faster to assemble than the compressed_matrix, but are 
> slower to traverse.
> 
> Before the computation of the sparsity pattern was implemented, DOLFIN 
> assembled into a uBLAS vector-of-compressed-vectors because it is quite 
> fast to assemble uninitialised and can be converted quite quickly to a 
> compressed row matrix. This approach may still have merit for some problems.
> 
> Garth

I think eventually we should assemble into a special-purpose data
structure that is fast for assembly and the convert row-wise (which is
fast) into something suitable for linear algebra.

-- 
Anders

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