On 3/21/07, Gary S. Thompson <[EMAIL PROTECTED]> wrote:
Edward d'Auvergne wrote:

> My personal experience with the coding of the grid computing code, I
> would assume that there are a number of differences.  For example the
> algorithm relax currently uses to handle computers of different
> speeds.

This should not make a difference you just divide more finely and weight
the size of the job by computer (you can even send off the finer grained
task one at a time and then send new ones as tasks are completed... the
same way as you do in the thread code)

The model-free problem places a lower bound on the minimum granularity
size.  That limit is the optimisation instance.  For almost all
minimisation techniques (the grid search excluded) parallelisation is
not possible.  Say you have a calculation which would take 20 min on a
3 GHz machine but it is sent to a 500 MHz old clunker in the basement.
These are serious performance issues in a grid that add up - they
need to be handled properly and not solely by making the calculations
more fine grained.  And a couple of those old machines in addition to
the fast ones could significantly speed up model-free analysis.


> Grid computing is designed for a heterogeneous environment
> whereas MPI is not.  I'm not saying one is superior to the other but
> that they have different applications in different computing
> environments.


mpi can cope with a hetrogeneous environment as explained above

Not well though.  And a likely scenario - a Windows user turning off
their machine when they go home rather than just logging out - is not
something MPI is designed for.  It is a tool which can be fitted into
these situations, but in this case it isn't the best tool for the job.
Grid computing is the best tool.  In the situation of a roughly
homogeneous fault-free environment or a cluster, grid computing is not
the best tool, MPI is.

Cheers,

Edward

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