On Thu, Apr 24, 2008 at 12:56:03PM +0200, Ingo Josopait wrote:
I am using one of the nodes as a desktop computer. Therefore it is
most
important for me that the mpi program is not so greedily acquiring
cpu
time.
This is a kernel scheduling issue, not an OpenMPI issue. Busy
waiting in
one process should not cause noticable loss of responsiveness in
another
processes. Have you experimented with the "nice" command?
But I would imagine that the energy consumption is generally a big
issue, since energy is a major cost factor in a computer cluster.
Yup.
When a
cpu is idle, it uses considerably less energy. Last time I checked
my
computer used 180W when both cpu cores were working and 110W when
both
cores were idle.
What processor is this?
I just made a small hack to solve the problem. I inserted a simple
sleep
call into the function 'opal_condition_wait':
--- orig/openmpi-1.2.6/opal/threads/condition.h
+++ openmpi-1.2.6/opal/threads/condition.h
@@ -78,6 +78,7 @@
#endif
} else {
while (c->c_signaled == 0) {
+ usleep(1000);
opal_progress();
}
}
I expect this would lead to increased execution time for all programs
and increased energy consumption for most programs. Recall that
energy
is power multiplied by time. You're reducing the power on some nodes
and increasing time on all nodes.
The usleep call will let the program sleep for about 4 ms (it won't
sleep for a shorter time because of some timer granularity). But
that is
good enough for me. The cpu usage is (almost) zero when the tasks
are
waiting for one another.
I think your mistake here is considering CPU load to be a useful
metric.
It isn't. Responsiveness is a useful metric, energy is a useful
metric,
but CPU load isn't a reliable guide to either of these.
For a proper implementation you would want to actively poll
without a
sleep call for a few milliseconds, and then use some other method
that
sleeps not for a fixed time, but until new messages arrive.
Well, it sounds like you can get to this before I can. Post your
patch
here and I'll test it on the NAS suite, UMT2K, Paradis, and a few
synthetic benchmarks I've written. The cluster I use has multimeters
hooked up so I can also let you know how much energy is being saved.
Barry Rountree
Ph.D. Candidate, Computer Science
University of Georgia
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