On Jan 28, 2013, at 8:25 AM, Maxime Boissonneault <maxime.boissonneault_at_[hidden]> 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?
> 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.
Sorry we can't be of more help :-(
> 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.
>> On Jan 28, 2013, at 7:47 AM, Maxime Boissonneault <maxime.boissonneault_at_[hidden]> wrote:
>>> 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 ?
>>> Maxime Boissonneault
>>> Analyste de calcul - Calcul Québec, Université Laval
>>> Ph. D. en physique
>>> users mailing list
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> Maxime Boissonneault
> Analyste de calcul - Calcul Québec, Université Laval
> Ph. D. en physique