Hello friendly people,
my question is rather specific.
For more than a week, I am trying to submit thousands of single thread jobs for a scientific experiment using sbatch and srun.
The problem is that these jobs may take different amounts of time to finish and some may even be aborted as they exceed the memory limit. Both behaviors are fine and my evaluation deals with it.
But, I am facing the problem that some of the jobs are never started, even though they have been submitted.
My sbatch script looks like this:
#!/usr/bin/bash
#SBATCH --nodes=4
#SBATCH --tasks-per-node=12
#SBATCH --mem-per-cpu=10000
for i in {1..500}
do
srun -N1 -n1 -c1 --exclusive --time=60 ${mybinary} $i &
wait 5s
done
Now, my error log shows the following message:
srun: Job 1846955 step creation temporarily disabled, retrying
1) What does 'step creation temporarily disabled' mean? Are all cpu's busy and the job is omitted or is it started again later when resources are free?
2) Why are some of my jobs not carried out and how can I fix it? Do I use the correct parameters for srun?
Thanks for your help!
srun: Job 1846955 step creation temporarily disabled, retrying
This is normal, you reserve 4 x 12 CPUs and start 500 instances of srun. Only 48 instances will run, while the other will output that message. Whenever a running instance stops, a pending instance starts.
wait 5s
The wait command is used to wait for processes, not for a certain amount of time. For that, use the sleep command. The wait command must be at the end of the script. Otherwise, the job could stop before all srun instances have finished.
So the scrip should look like this:
#!/usr/bin/bash
#SBATCH --nodes=4
#SBATCH --tasks-per-node=12
#SBATCH --mem-per-cpu=10000
for i in {1..500}
do
srun -N1 -n1 -c1 --exclusive --time=60 ${mybinary} $i &
done
wait
Related
I have seen the following two very similar schemes used when submitting jobs with multiple steps to slurm:
On the one hand you can do
#SBATCH -N1 -c1 -n5 # 5 tasks in total on 1 node, 1 cpu per task
for j in {1..4}; do
srun --exclusive -n1 script $j &
done
srun --exclusive -n1 script 5
wait
On the other hand you can do
#SBATCH -N1 -c1 -n5 # 5 tasks in total on 1 node, 1 cpu per task
for j in {1..5}; do
srun --exclusive -n1 script $j &
done
wait
Because the job should have only 5 CPUs allocated to it I don't really
understand how the second one can work correctly, since after
four job steps have been started with srun there is no way the scheduler can allocate a fifth job 'in the background' and then return to the original script... where would the original script run? (I admit my knowledge of these things is pretty limited though).
However, I have personally tested both ways and they both seem to work exactly the same. The second script is a bit simpler in my opinion, and when dealing with somewhat larger input scripts this can be an advantage, but I'm worried that I don't understand 100% what is going on here. Is there a preferred way to do this? What is the difference? What is Bash/slurm doing behind the scenes?
They both work the same in principle, though the second one is clearer (and correct - see below). Each invocation of srun will run script on a separate CPU (probably - though if it runs very fast they could run on a subset of the sbatch-allocated CPUs).
I think the first example doesn't need wait, since the last command isn't run in the background.
By the way, the first example has an error: %j is local to the for-loop, so the last run inside the loop and the run outside the loop both invoke script 4.
I found some very similar questions which helped me arrive at a script which seems to work however I'm still unsure if I fully understand why, hence this question..
My problem (example): On 3 nodes, I want to run 12 tasks on each node (so 36 tasks in total). Also each task uses OpenMP and should use 2 CPUs. In my case a node has 24 CPUs and 64GB memory. My script would be:
#SBATCH --nodes=3
#SBATCH --ntasks=36
#SBATCH --cpus-per-task=2
#SBATCH --mem-per-cpu=2000
export OMP_NUM_THREADS=2
for i in {1..36}; do
srun -N 1 -n 1 ./program input${i} >& out${i} &
done
wait
This seems to work as I require, successively running tasks on a node until all CPUs on that node are in use, and then continuing to run further tasks on the next node until all CPUs are used again, etc..
My question.. I'm not sure if this is actually what it does (?) as I didn't fully understand the man page of srun regarding -n, and i have not used srun before.
Mainly my confusion comes from "-n": In the man page for -n it says "The default is one task per node, ..", so I expected if I use "srun -n 1" that only one task will be run on each node, which doesn't seem to be the case.
Furthermore when i tried e.g. "srun -n 2 ./program" it seems to just run the exact same program twice as two different tasks with no way to use different input files.. which I can't think of why that would ever be useful?
Your setup is correct except that you must use the --exclusive option of srun (which has a different meaning in this case than for sbatch).
As for your remark regarding the usefulness of srun, the behaviour of the program can be changed based on the environment variable $SLURM_TASK_ID, or the rank in case of an MPI program. Your confusion arises from the fact that your program is not written to be parallel (appart from the 2 OMP threads) while srun is meant to start parallel programs, most of the time based on MPI.
An other way is to run all your tasks at once.
since the input and output file depends on the rank, a wrapper is needed
your SLURM script would be
#SBATCH --nodes=3
#SBATCH --ntasks=36
#SBATCH --cpus-per-task=2
#SBATCH --mem-per-cpu=2000
export OMP_NUM_THREADS=2
srun -n 36 ./program.sh
and your wrapper program.sh would be
#!/bin/sh
exec ./program input${SLURM_PROCID} > out${SLURM_PROCID} 2>&1
I'm trying to run a Particle Swarm Optimization problem on a cluster using SLURM, with the optimization algorithm managed by a single-core matlab process. Each particle evaluation requires multiple MPI calls that alternate between two Python programs until the result converges. Each MPI call takes up to 20 minutes.
I initially naively submitted each MPI call as a separate SLURM job, but the resulting queue time made it slower than running each job locally in serial. I am now trying to figure out a way to submit an N node job that will continuously run MPI tasks to utilize the available resources. The matlab process would manage this job with text file flags.
Here is a pseudo-code bash file that might help to illustrate what I am trying to do on a smaller scale:
#!/bin/bash
#SBATCH -t 4:00:00 # walltime
#SBATCH -N 2 # number of nodes in this job
#SBATCH -n 32 # total number of processor cores in this job
# Set required modules
module purge
module load intel/16.0
module load gcc/6.3.0
# Job working directory
echo Working directory is $SLURM_SUBMIT_DIR
cd $SLURM_SUBMIT_DIR
echo Running on host `hostname`
echo Time is `date`
echo Directory is `pwd`
# Run Command
while <"KeepRunning.txt” == 1>
do
for i in {0..40}
do
if <“RunJob_i.txt” == 1>
then
mpirun -np 8 -rr -f ${PBS_NODEFILE} <job_i> &
fi
done
done
wait
This approach doesn't work (just crashes), but I don't know why (probably overutilization of resources?). Some of my peers have suggested using parallel with srun, but as far as I can tell this requires that I call the MPI functions in batches. This will be a huge waste of resources, as a significant portion of the runs finish or fail quickly (this is expected behavior). A concrete example of the problem would be starting a batch of 5 8-core jobs and having 4 of them crash immediately; now 32 cores would be doing nothing while they wait up to 20 minutes for the 5th job to finish.
Since the optimization will likely require upwards of 5000 mpi calls, any increase in efficiency will make a huge difference in absolute walltime. Does anyone have any advice as to how I could run a constant stream of MPI calls on a large SLURM job? I would really appreciate any help.
A couple of things: under SLURM you should be using srun, not mpirun.
The second thing is that the pseudo-code you provided launches an infinite number of jobs without waiting for any completion signal. You should try to put the wait into the inner loop, so you launch just a set of jobs, wait for them to finish, evaluate the condition and, maybe, launch the next set of jobs:
#!/bin/bash
#SBATCH -t 4:00:00 # walltime
#SBATCH -N 2 # number of nodes in this job
#SBATCH -n 4 # total number of tasks in this job
#SBATCH -s 8 # total number of processor cores for each task
# Set required modules
module purge
module load intel/16.0
module load gcc/6.3.0
# Job working directory
echo Working directory is $SLURM_SUBMIT_DIR
cd $SLURM_SUBMIT_DIR
echo Running on host `hostname`
echo Time is `date`
echo Directory is `pwd`
# Run Command
while <"KeepRunning.txt” == 1>
do
for i in {0..40}
do
if <“RunJob_i.txt” == 1>
then
srun -np 8 --exclusive <job_i> &
fi
done
wait
<Update "KeepRunning.txt”>
done
Take care also distinguishing tasks and cores. -n says how many tasks will be used, -c says how many cpus per task will be allocated.
The code I wrote will launch in the background 41 jobs (from 0 to 40, included), but they will only start once the resources are available (--exclusive), waiting while they are occupied. Each jobs will use 8 CPUs. The you will wait for them to finish and I assume that you will update the KeepRunning.txt after that round.
I was using SLURM to use some computing cluster and it had the -ntasks or -n. I have obviously read the documentation for it (http://slurm.schedmd.com/sbatch.html):
sbatch does not launch tasks, it requests an allocation of resources
and submits a batch script. This option advises the Slurm controller
that job steps run within the allocation will launch a maximum of
number tasks and to provide for sufficient resources. The default is
one task per node, but note that the --cpus-per-task option will
change this default.
the specific part I do not understand what it means is:
run within the allocation will launch a maximum of number tasks and to
provide for sufficient resources.
I have a few questions:
I guess my first question is what does the word "task" mean and the difference is with the word "job" in the SLURM context. I usually think of a job as the running the bash script under sbatch as in sbatch my_batch_job.sh. Not sure what task means.
If I equate the word task with job then I thought it would have ran the same identical bash script multiple times according to the argument to -n, --ntasks=<number>. However, I obviously tested it out in the cluster, ran a echo hello with --ntask=9 and I expected sbatch would echo hello 9 times to stdout (which is collected in slurm-job_id.out, but to my surprise, there was a single execution of my echo hello script Then what does this command even do? It seems it does nothing or at least I can't see whats suppose to be doing.
I do know the -a, --array=<indexes> option exists for multiple jobs. That is a different topic. I simply want to know what --ntasks is suppose to do, ideally with an example so that I can test it out in the cluster.
The --ntasks parameter is useful if you have commands that you want to run in parallel within the same batch script.
This may be two separate commands separated by an & or two commands used in a bash pipe (|).
For example
Using the default ntasks=1
#!/bin/bash
#SBATCH --ntasks=1
srun sleep 10 &
srun sleep 12 &
wait
Will throw the warning:
Job step creation temporarily disabled, retrying
The number of tasks by default was specified to one, and therefore the second task cannot start until the first task has finished.
This job will finish in around 22 seconds. To break this down:
sacct -j515058 --format=JobID,Start,End,Elapsed,NCPUS
JobID Start End Elapsed NCPUS
------------ ------------------- ------------------- ---------- ----------
515058 2018-12-13T20:51:44 2018-12-13T20:52:06 00:00:22 1
515058.batch 2018-12-13T20:51:44 2018-12-13T20:52:06 00:00:22 1
515058.0 2018-12-13T20:51:44 2018-12-13T20:51:56 00:00:12 1
515058.1 2018-12-13T20:51:56 2018-12-13T20:52:06 00:00:10 1
Here task 0 started and finished (in 12 seconds) followed by task 1 (in 10 seconds). To make a total user time of 22 seconds.
To run both of these commands simultaneously:
#!/bin/bash
#SBATCH --ntasks=2
srun --ntasks=1 sleep 10 &
srun --ntasks=1 sleep 12 &
wait
Running the same sacct command as specified above
sacct -j 515064 --format=JobID,Start,End,Elapsed,NCPUS
JobID Start End Elapsed NCPUS
------------ ------------------- ------------------- ---------- ----------
515064 2018-12-13T21:34:08 2018-12-13T21:34:20 00:00:12 2
515064.batch 2018-12-13T21:34:08 2018-12-13T21:34:20 00:00:12 2
515064.0 2018-12-13T21:34:08 2018-12-13T21:34:20 00:00:12 1
515064.1 2018-12-13T21:34:08 2018-12-13T21:34:18 00:00:10 1
Here the total job taking 12 seconds. There is no risk of jobs waiting for resources as the number of tasks has been specified in the batch script and therefore the job has the resources to run this many commands at once.
Each task inherits the parameters specified for the batch script. This is why --ntasks=1 needs to be specified for each srun task, otherwise each task uses --ntasks=2 and so the second command will not run until the first task has finished.
Another caveat of the tasks inheriting the batch parameters is if --export=NONE is specified as a batch parameter. In this case --export=ALL should be specified for each srun command otherwise environment variables set within the sbatch script are not inherited by the srun command.
Additional notes:
When using bash pipes, it may be necessary to specify --nodes=1 to prevent commands either side of the pipes running on separate nodes.
When using & to run commands simultaneously, the wait is vital. In this case, without the wait command, task 0 would cancel itself, given task 1 completed successfully.
The "--ntasks" options specifies how many instances of your command are executed.
For a common cluster setup and if you start your command with "srun" this corresponds to the number of MPI ranks.
In contrast the option "--cpus-per-task" specify how many CPUs each task can use.
Your output surprises me as well. Have you launched your command in the script or via srun?
Does you script look like:
#!/bin/bash
#SBATCH --ntasks=8
## more options
echo hello
This should always output only a single line, because the script is only executed on the submitting node not the worker.
If your script look like
#!/bin/bash
#SBATCH --ntasks=8
## more options
srun echo hello
srun causes the script to run your command on the worker nodes and as a result you should get 8 lines of hello.
Tasks are processes that a job executes in parallel in one or more nodes. sbatch allocates resources for your job, but even if you request resources for multiple tasks, it will launch your job script in a single process in a single node only. srun is used to launch job steps from the batch script. --ntasks=N instructs srun to execute N copies of the job step.
For example,
#SBATCH --ntasks=2
#SBATCH --cpus-per-task=2
means that you want to run two processes in parallel, and have each process access two CPUs. sbatch will allocate four CPUs for your job and then start the batch script in a single process. Within your batch script, you can create a parallel job step using
srun --ntasks=2 --cpus-per-task=2 step.sh
This will run two processes in parallel, both of them executing the step.sh script. From the same job, you could also run
srun --ntasks=1 --cpus-per-task=4 step.sh
This would launch a single process that can access all the four GPUs (although it would issue a warning).
It's worth noting that within the allocated resources, your job script is free to do anything, and it doesn't have to use srun to create job steps (but you need srun to launch a job step in multiple nodes). For example, the following script will run both steps in parallel:
#!/bin/bash
#SBATCH --ntasks=1
step1.sh &
step2.sh &
wait
If you want to launch job steps using srun and have two different steps run in parallel, then your job needs to allocate two tasks, and your job steps need to request only one task. You also need to provide the --exclusive argument to srun, for the job steps to use separate resources.
#!/bin/bash
#SBATCH --ntasks=2
srun --ntasks=1 --exclusive step1.sh &
srun --ntasks=1 --exclusive step2.sh &
wait
I am trying to launch a large number of job steps using a batch script. The different steps can be completely different programs and do need exactly one CPU each. First I tried doing this using the --multi-prog argument to srun. Unfortunately, when using all CPUs assigned to my job in this manner, performance degrades massively. The run time increases to almost its serialized value. By undersubscribing I could ameliorate this a little. I couldn't find anything online regarding this problem, so I assumed it to be a configuration problem of the cluster I am using.
So I tried going a different route. I implemented the following script (launched via sbatch my_script.slurm):
#!/bin/bash
#SBATCH -o $HOME/slurm/slurm_out/%j.%N.out
#SBATCH --error=$HOME/slurm/slurm_out/%j.%N.err_out
#SBATCH --get-user-env
#SBATCH -J test
#SBATCH -D $HOME/slurm
#SBATCH --export=NONE
#SBATCH --ntasks=48
NR_PROCS=$(($SLURM_NTASKS))
for PROC in $(seq 0 $(($NR_PROCS-1)));
do
#My call looks like this:
#srun --exclusive -n1 bash $PROJECT/call_shells/call_"$PROC".sh &
srun --exclusive -n1 hostname &
pids[${PROC}]=$! #Save PID of this background process
done
for pid in ${pids[*]};
do
wait ${pid} #Wait on all PIDs, this returns 0 if ANY process fails
done
I am aware, that the --exclusive argument is not really needed in my case. The shell scripts called contain the different binaries and their arguments. The remaining part of my script relies on the fact that all processes have finished hence the wait. I changed the calling line to make it a minimal working example.
At first this seemed to be the solution. Unfortunately when increasing the number of nodes used in my job allocation (for example by increasing --ntasks to a number larger than the number of CPUs per node in my cluster), the script does not work as expected anymore, returning
srun: Warning: can't run 1 processes on 2 nodes, setting nnodes to 1
and continuing using only one node (i.e. 48 CPUs in my case, which go through the job steps as fast as before, all processes on the other node(s) are subsequently killed).
This seems to be the expected behaviour, but I can't really understand it. Why is it that every job step in a given allocation needs to include a minimum number of tasks equal to the number of nodes included in the allocation. I ordinarily really do not care at all about the number of nodes used in my allocation.
How can I implement my batch script, so it can be used on multiple nodes reliably?
Found it! The nomenclature and the many command line options to slurm confused me. The solution is given by
#!/bin/bash
#SBATCH -o $HOME/slurm/slurm_out/%j.%N.out
#SBATCH --error=$HOME/slurm/slurm_out/%j.%N.err_out
#SBATCH --get-user-env
#SBATCH -J test
#SBATCH -D $HOME/slurm
#SBATCH --export=NONE
#SBATCH --ntasks=48
NR_PROCS=$(($SLURM_NTASKS))
for PROC in $(seq 0 $(($NR_PROCS-1)));
do
#My call looks like this:
#srun --exclusive -N1 -n1 bash $PROJECT/call_shells/call_"$PROC".sh &
srun --exclusive -N1 -n1 hostname &
pids[${PROC}]=$! #Save PID of this background process
done
for pid in ${pids[*]};
do
wait ${pid} #Wait on all PIDs, this returns 0 if ANY process fails
done
This specifies to run the job on exactly one node incorporating a single task only.