On Sat, 22 Mar 2008, Ellis Wilson wrote:
I'm very interested to hear of some applications for
such loosely connected "clusters" such as boinc would
create. My crappy 100mb connection is alright for the
few embarrassingly parallel applications I've applied
to it which do not have a large origin dataset, but
again, these are very few. I would imagine the
connection (with hops and an even slower/less
dedicated interconnect at each hop) for boinc "nodes"
would be far worse. I looked for examples on the
boinc site briefly, but cannot seem to find any.
Any notable embarrassingly parallel problems you all
have seen or worked with? Sorry for my lack of
experience in this area.
Almost all importance sampling Monte Carlo computations fit into the
category of stuff that works wonderfully on anything from sneakernet on
up. I used to distribute jobs on with tcl/expect scripts running over
rsh and 10 Mbps ethernet back in the early to mid 90's. Lots of other
physics computations are one CPU, one job, but a large parameter space
to be investigated with many jobs. Random number generator testing
could be parallelized nicely with very low bandwidth connections
(although I haven't even thought seriously about parallelizing dieharder
yet -- it's difficult enough to mess with the code as serial
modular tests so far). Lots of graphical processing fits in a category
that will work, although some does start getting up into bw intensive as
well -- it depends as always on the granularity and ratio of computation
to communication for the specific task.
In general code that requires only "small data" for startup and that
spans a large parametric space with that small data, that takes a
substantial amount of time to run a computation from that data, and that
returns (say) a small vector of numbers to a central aggregator in a
master-slave sort of computation is a very reasonable candidate for this
sort of cluster. I ran code for years that I used to joke about
distributing on [EMAIL PROTECTED];-)
rgb
Ellis
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