Here at the Upper Midwest Environmental Sciences Center we are evaluating
the potential for developing a Linux-based BUGS. Our interest is in
speeding up processing from what currently takes nearly 3 days per run
(with final models historically averaging nearly one month of development
time). We hope that by creating "LinBUGS" we might be able to implement a
clustered-processing approach whereby we share the simulations across a
number of computers. A simplistic approach would be running single chains
on individual computers and then combining them post hoc. Another approach
might be to actually split some of the processing within chains across
multiple computers; it is this latter approach that would harness the power
of clustered computing. Before we go off on some goose chase, I would like
to hear from the BUGS community about this issue. If you have previously
considered or implemented a clustered-computing approach for BUGS, please
contact me. Also, I'm rather interested in whether others feel processing
time currently constrains the questions one might ask. We currently run
our models on machines (1 gb RAM, 1.80 GHz processing speed) that aren't
puny; each iteration takes on the order of 17 seconds. Because convergence
on most of the spatial models I'm working with doesn't occur until
somewhere around 18,000 iterations, that's 2.8 days in a single run.
Thanks for any discussion this might generate,
Wayne E. Thogmartin, PhD
Statistician (Biology)
USGS Upper Midwest Environmental Sciences Center
2630 Fanta Reed Road
La Crosse, WI 54603
608.781.6309
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www.umesc.usgs.gov/staff/bios/wet0.html
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