Le 2013-01-28 13:15, Ralph Castain a écrit :
On Jan 28, 2013, at 9:52 AM, Maxime Boissonneault
<maxime.boissonnea...@calculquebec.ca> wrote:
Le 2013-01-28 12:46, Ralph Castain a écrit :
On Jan 28, 2013, at 8:25 AM, Maxime Boissonneault
<maxime.boissonnea...@calculquebec.ca> wrote:
Hello Ralph,
I agree that ideally, someone would implement checkpointing in the application
itself, but that is not always possible (commercial applications, use of
complicated libraries, algorithms with no clear progression points at which you
can interrupt the algorithm and start it back from there).
Hmmm...well, most apps can be adjusted to support it - we have some very
complex apps that were updated that way. Commercial apps are another story, but
we frankly don't find much call for checkpointing those as they typically just
don't run long enough - especially if you are only running 256 ranks, so your
cluster is small. Failure rates just don't justify it in such cases, in our
experience.
Is there some particular reason why you feel you need checkpointing?
This specific case is that the jobs run for days. The risk of a hardware or
power failure for that kind of duration goes too high (we allow for no more
than 48 hours of run time).
I'm surprised by that - we run with UPS support on the clusters, but for a
small one like you describe, we find the probability that a job will be
interrupted even during a multi-week app is vanishingly small.
FWIW: I do work with the financial industry where we regularly run apps that
execute non-stop for about a month with no reported failures. Are you actually
seeing failures, or are you anticipating them?
While our filesystem and management nodes are on UPS, our compute nodes
are not. With one average generic (power/cooling mostly) failure every
one or two months, running for weeks is just asking for trouble. If you
add to that typical dimm/cpu/networking failures (I estimated about 1
node goes down per day because of some sort hardware failure, for a
cluster of 960 nodes). With these numbers, a job running on 32 nodes for
7 days has a ~35% chance of failing before it is done.
Having 24GB of ram per node, even if a 32 nodes job takes close to 100%
of the ram, that's merely 640 GB of data. Writing that on a lustre
filesystem capable of reaching ~15GB/s should take no more than a few
minutes if written correctly. Right now, I am getting a few minutes for
a hundredth of this amount of data!
While it is true we can dig through the code of the library to make it
checkpoint, BLCR checkpointing just seemed easier.
I see - just be aware that checkpoint support in OMPI will disappear in v1.7
and there is no clear timetable for restoring it.
That is very good to know. Thanks for the information. It is too bad though.
There certainly must be a better way to write the information down on disc
though. Doing 500 IOPs seems to be completely broken. Why isn't there buffering
involved ?
I don't know - that's all done in BLCR, I believe. Either way, it isn't
something we can address due to the loss of our supporter for c/r.
I suppose I should contact BLCR instead then.
For the disk op problem, I think that's the way to go - though like I said, I
could be wrong and the disk writes could be something we do inside OMPI. I'm
not familiar enough with the c/r code to state it with certainty.
Thank you,
Maxime
Sorry we can't be of more help :-(
Ralph
Thanks,
Maxime
Le 2013-01-28 10:58, Ralph Castain a écrit :
Our c/r person has moved on to a different career path, so we may not have
anyone who can answer this question.
What we can say is that checkpointing at any significant scale will always be a losing
proposition. It just takes too long and hammers the file system. People have been working
on extending the capability with things like "burst buffers" (basically putting
an SSD in front of the file system to absorb the checkpoint surge), but that hasn't
become very common yet.
Frankly, what people have found to be the "best" solution is for your app to periodically
write out its intermediate results, and then take a flag that indicates "read prior
results" when it starts. This minimizes the amount of data being written to the disk. If done
correctly, you would only lose whatever work was done since the last intermediate result was
written - which is about equivalent to losing whatever works was done since the last checkpoint.
HTH
Ralph
On Jan 28, 2013, at 7:47 AM, Maxime Boissonneault
<maxime.boissonnea...@calculquebec.ca> wrote:
Hello,
I am doing checkpointing tests (with BLCR) with an MPI application compiled
with OpenMPI 1.6.3, and I am seeing behaviors that are quite strange.
First, some details about the tests :
- The only filesystem available on the nodes are 1) one tmpfs, 2) one lustre
shared filesystem (tested to be able to provide ~15GB/s for writing and support
~40k IOPs).
- The job was running with 8 or 16 MPI ranks on nodes with 8 cores (1 or 2
nodes). Each MPI rank was using approximately 200MB of memory.
- I was doing checkpoints with ompi-checkpoint and restarting with ompi-restart.
- I was starting with mpirun -am ft-enable-cr
- The nodes are monitored by ganglia, which allows me to see the number of IOPs
and the read/write speed on the filesystem.
I tried a few different mca settings, but I consistently observed that :
- The checkpoints lasted ~4-5 minutes each time
- During checkpoint, each node (8 ranks) was doing ~500 IOPs, and writing at
~15MB/s.
I am worried by the number of IOPs and the very slow writing speed. This was a
very small test. We have jobs running with 128 or 256 MPI ranks, each using 1-2
GB of ram per rank. With such jobs, the overall number of IOPs would reach tens
of thousands and would completely overload our lustre filesystem. Moreover,
with 15MB/s per node, the checkpointing process would take hours.
How can I improve on that ? Is there an MCA setting that I am missing ?
Thanks,
--
---------------------------------
Maxime Boissonneault
Analyste de calcul - Calcul Québec, Université Laval
Ph. D. en physique
_______________________________________________
users mailing list
us...@open-mpi.org
http://www.open-mpi.org/mailman/listinfo.cgi/users
_______________________________________________
users mailing list
us...@open-mpi.org
http://www.open-mpi.org/mailman/listinfo.cgi/users
--
---------------------------------
Maxime Boissonneault
Analyste de calcul - Calcul Québec, Université Laval
Ph. D. en physique
--
---------------------------------
Maxime Boissonneault
Analyste de calcul - Calcul Québec, Université Laval
Ph. D. en physique
--
---------------------------------
Maxime Boissonneault
Analyste de calcul - Calcul Québec, Université Laval
Ph. D. en physique
