Hello,
following the discussion at the end of todays workshop I tried how the
scheduler behaves when issuing a larger amount of jobs (Marcus
essentially told me I could use approach 3 as detailed below). To frame
my question, here is what want to do and how I try to do it (numbers
just to get the magnitude):
# Problem
10 Binaries, 10k input files. Run every binary on every input file, and
collect all the results (= parse stdout).
It seems array jobs are the tool for that, however the size of an array
job is capped at 1000, apparently because larger jobs make the scheduler
slow.
# Approach 1
- Create one file with 10*10k lines (./binary input-file)
- Create one job with 1000 array jobs
- Let ID be the id of the current array job
- Identify the slice (10*10k) / 1000 * ID .. (10*10k) / 1000 * (ID + 1)
- Execute all lines from the slice sequentially
- Pro: Only one job, no scheduling hassle on the user side.
- Con: weird script logic, 100 individual tasks in one scheduled array
job, sometimes bad load balancing (i.e. one job takes way longer than
the others)
# Approach 2
- Create (10*10k)/1000 files, each containing 1000 lines
- Create as many jobs, one for each file
- Load the ID'th line from the respective file and execute it
- Push all these jobs to the scheduler
- Pro: Easier logic in each script
- Con: Multiple job, I have to take care of submitting and waiting for
the results in parallel.
# Approach 3
- Create 10*10k jobs, let the scheduler deal with it
- Every job executes one task (./binary input-file)
- Pro: very simple jobs and scripts
- Con: huge amount of jobs, can the scheduler handle that?
I'm using approach 1 already and it works somewhat fine. That being said
the script logic is rather involved and load balancing is not that
great. I routinely have a handful of jobs at the end that run for 10
minutes or so longer than all the others where a single task is capped
at one minute. This is pretty annoying. Also, we are exploring what the
best-practice should be here...
I just tried approach 2 and it did not go to well, even for only about
12k tasks. To try the scaling I made every array job 100 in size, so I
tried to schedule about 120 jobs.
While it went well for about 75 jobs, sbatch started to come back with
the following afterwards:
sbatch: error: Slurm temporarily unable to accept job, sleeping and retrying
and quickly afterwards:
sbatch: error: Batch job submission failed: Resource temporarily unavailable
I then tried to "relax" a bit and added a one second delay between the
calls to sbatch... and it does not change everything.
Thus I don't have a lot of hope for approach 3...
Any comments or ideas?
Best,
Gereon
--
Gereon Kremer
Lehr- und Forschungsgebiet Theorie Hybrider Systeme
RWTH Aachen
Tel: +49 241 80 21243
Hello,
Is it possible to activate X11-Forwaring on a job submitted via SLURM?
LSF had the Option in
#BSUB -XF
But I cannot find anything equivalent for SLURM in the documentation
For some commercial applications like Wolfram Mathematica or Abaqus I would
need the GUI interface to run my jobs.
Also I should add, that i would like to run these Applications in parallel
with OpenMP, which was possible on LSF.
Is it not planned to supply this feature?
Best Regards,
Marek
Dear admins and users,
I'm using the Wien2k DFT code, which is basically a suite of various
subprograms each one doing one specific thing glued together by various
c shell scripts. There are parallellized at a hybrid MPI/openMP level
(+ some parts just spawn multiple nonMPI processes with OpenMP
threads). The problem is that various subtasks need different number of
MPI/openMP processes/threads for optimal speed.
I call the software by csh script run_lapw which will in turn call
programs like lapw0, lapw1, lapw2 and mixer.
The Wien2k c shell glue is doing the parallelization of subprograms
dispatch based on some internal configuration files which I'm
generating on the fly based on the actual allocated nodes as obtained
from SLURM. It sets the OMP_NUM_THREADS properly and calls the mpirun
with the correct number of processes and proper -machinefile <file>
generated based on the input from SLURM and optimal configuration for
each subprogram.
Some specific examples of optimal parallelization for the 48cpu node
for different subprograms being called from indide the run_lapw script:
- 8 MPI processes with 12omp threads each
- 32 noncomunicating processes with 2omp threads
- 49 MPI processes without threading
- single process with 48 omp threads
However what I see sometime is that the mpirun calls (intelmpi) from
the c shell scripts are intercepted and modified resulting in multiple
CPU processes (threads) being bound to single CPU and suboptimal
performance.
So basically I need a way to tell the SLURM to just allocate me a full
node and not mess up the mpirun calls from inside the csh scripts or
don't do any CPU pinning...
Any advice would be appreciated.
Best regards
Pavel Ondračka
Hi,
for our simulations we have a simulation manager. For LSF this used to
issue a bsub command for each simulation. We're not using array jobs for
this as it has some more requirements.
According to
https://doc.itc.rwth-aachen.de/download/attachments/39160017/Slurm%20and%20…
I can not simply replace bsub with srun, I need to do a sbatch.
I believe this should work: Run the simulation manager with sbatch, then
it should be able to do srun for the different simulations.
Will this work?
Best
Johannes
--
M.Sc. Johannes Sauer
Researcher
Institut fuer Nachrichtentechnik
RWTH Aachen University
Melatener Str. 23
52074 Aachen
Tel +49 241 80-27678
Fax +49 241 80-22196
sauer(a)ient.rwth-aachen.de
http://www.ient.rwth-aachen.de
Dear Users,
there will be now a short period, when you cannot submit jobs and no
jobs get scheduled.
With kind regards
Marcus Wagner
--
Marcus Wagner, Dipl.-Inf.
IT Center
Abteilung: Systeme und Betrieb
RWTH Aachen University
Seffenter Weg 23
52074 Aachen
Tel: +49 241 80-24383
Fax: +49 241 80-624383
wagner(a)itc.rwth-aachen.de
www.itc.rwth-aachen.de
Dear users,
thanks to several reports we have discovered a problem when trying to
submit multi-node jobs that request more than 24 tasks per node. In
general a resource request looking like this should work perfectly fine:
(...)
#SBATCH --nodes=5
#SBATCH --ntasks-per-node=48
(...)
Theoretically this would allow you to make full use of 5 nodes.
Currently, however, sbatch rejects such job scripts claiming that there
were no hosts suitable for dispatchment. Despite this, the following
request
(...)
#SBATCH --ntasks=240
(...)
works as intended while being semantically equal in this scenario. We
are not sure exactly what is causing this problem but do suspect a bug
in slurm, possibly in conjunction with the Skylake-SP CPUs. If you are
affected, we recommend to use --ntasks only for the time being. We will
change the documentation accordingly so that you can build your job
scripts upon correct templates. The problem has been relayed to the
developers, we will have to wait for their assessment.
Please excuse any inconvenience.
Best,
Sven
--
Sven Hansen
IT Center
Abteilung: Systeme und Betrieb
RWTH Aachen University
Seffenter Weg 23
52074 Aachen (Germany)
Tel.: + 49 241 80-29114
s.hansen(a)itc.rwth-aachen.de
www.itc.rwth-aachen.de
Hello Marcus,
unfortunately I get essentially the same problem. srun spawns #cores instances of the CFX solver, every one of which tries to access all cores.
Since they still try to communicate with the other node over ssh the result is the same error as below.
Regards,
Thomas
Von: Marcus Wagner [mailto:wagner@itc.rwth-aachen.de]
Gesendet: Dienstag, 12. Februar 2019 15:21
An: claix18-slurm-pilot(a)lists.rwth-aachen.de
Betreff: [claix18-slurm-pilot] Re: Multi-Node ANSYS simulations
Dear Thomas,
could you please test the following:
srun cfx5solve -batch -parallel -partition $SLURM_NTASKS -def job.def -par-dist "$CFXHOSTS" -start-method "Intel MPI Distributed Parallel".
Best
Marcus
On 2/12/19 11:10 AM, Gier, Thomas wrote:
Hello,
I'm having issues running ANSYS CFX calculations across multiple nodes.
Single-node simulations run fine, but multi-node configurations crash because ssh connections are being denied:
" +--------------------------------------------------------------------+
| An error has occurred in cfx5solve: |
| |
| Remote connection to ncm0791.hpc.itc.rwthaachen.de |
| (ncm0791.hpc.itc.rwth-aachen.de) could not be started, or exited |
| with return code 255. It gave the following output: |
| |
| Permission denied (publickey,gssapi-keyex,gssapi-with-mic,pass- |
| word,hostbased). |
| |
| Check that you have typed the hostname correctly, and that you |
| have an account "tg084461" on the specified host with access |
| permission from this host. You can use the following command to |
| check the connection to a UNIX machine: |
| |
| ssh ncm0791.hpc.itc.rwth-aachen.de uname |
+--------------------------------------------------------------------+"
Am I missing something in my submission script, or is this a cluster config issue?
Regards,
Thomas Gier
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--
Marcus Wagner, Dipl.-Inf.
IT Center
Abteilung: Systeme und Betrieb
RWTH Aachen University
Seffenter Weg 23
52074 Aachen
Tel: +49 241 80-24383
Fax: +49 241 80-624383
wagner(a)itc.rwth-aachen.de<mailto:wagner@itc.rwth-aachen.de>
www.itc.rwth-aachen.de<http://www.itc.rwth-aachen.de>
Hello,
I'm having issues running ANSYS CFX calculations across multiple nodes.
Single-node simulations run fine, but multi-node configurations crash because ssh connections are being denied:
" +--------------------------------------------------------------------+
| An error has occurred in cfx5solve: |
| |
| Remote connection to ncm0791.hpc.itc.rwthaachen.de |
| (ncm0791.hpc.itc.rwth-aachen.de) could not be started, or exited |
| with return code 255. It gave the following output: |
| |
| Permission denied (publickey,gssapi-keyex,gssapi-with-mic,pass- |
| word,hostbased). |
| |
| Check that you have typed the hostname correctly, and that you |
| have an account "tg084461" on the specified host with access |
| permission from this host. You can use the following command to |
| check the connection to a UNIX machine: |
| |
| ssh ncm0791.hpc.itc.rwth-aachen.de uname |
+--------------------------------------------------------------------+"
Am I missing something in my submission script, or is this a cluster config issue?
Regards,
Thomas Gier
Hi,
a few questions/points form my side:
- Claix 18 is using Intel OPA. What network topology is used? I guess it
is a Fat tree. Is it blocking or non-blocking? Is it 1:2 blocking as on
Claix 16?
- Have you configured topology-aware resource allocation within the
SLURM scheduler, in other words does the scheduler knows the topology
and tries to minimize the hop-count?
- I assume TurboBoost is enabled by default? Is it possible (or will it
be possible in the future) to include an option to switch TurboBoost
off? E.g. on JURECA it is possible to disable TurboBoost with `#SBATCH
--disable-turbomode` for measurements.
Otherwise it is possible to set frequencies with likwid?
- I tried to run jobs with 256 nodes. I am getting an MPI error (cf. job
92414):
nrm008.hpc.itc.rwth-aachen.de.233340PSM2 no hfi units are active (err=23)
[245] MPI startup(): tmi fabric is not available and fallback fabric is
not enabled
Any ideas where this is coming from? Should I manually adjust
I_MPI_FABRICS? I don't want to set the fallback fabric, since this would
be TCP and would significantly impact performance. Affected jobs are not
canceled but are running into the time limit.
Theses errors are only occurring on the nrm nodes, not on the ncm nodes.
Could there be a problem with the nrm nodes? Currently I am using the
partition c18m, which contains both nodes types. How can I only select
ncm nodes?
- Historic jobs can not be viewed with scontrol or sstat. sacct on the
other hand works. For example:
$ scontrol show job 90949
slurm_load_jobs error: Invalid job id specified
$ sstat --format=AveCPU,AvePages,AveRSS,AveVMSize,JobID -j 90945
AveCPU AvePages AveRSS AveVMSize JobID
---------- ---------- ---------- ---------- ------------
sstat: error: couldn't get steps for job 90945
- Some of my jobs don't appear in the queue and are not scheduled, even
if sbatch returns `Submitted batch job 92365`
- You are using a hand-build module system. One issue with this approach
is that dependencies are not dissolved properly. For example loading the
module python does something unexpected. A short example:
$ module load intel; ldd main.x | grep mkl
intel/19.0 already loaded, doing
nothing [ WARNING ]
libmkl_intel_lp64.so =>
/opt/intel/Compiler/19.0/1.144/rwthlnk/mkl/lib/intel64_lin/libmkl_intel_lp64.so
(0x00002ac58b9ee000)
libmkl_core.so =>
/opt/intel/Compiler/19.0/1.144/rwthlnk/mkl/lib/intel64_lin/libmkl_core.so
(0x00002ac58c53c000)
libmkl_intel_thread.so =>
/opt/intel/Compiler/19.0/1.144/rwthlnk/mkl/lib/intel64_lin/libmkl_intel_thread.so
(0x00002ac5906c8000)
$ module load python; ldd main.x | grep mkl
Loading python 2.7.12 [ OK ]
The SciPy Stack available: http://www.scipy.org/stackspec.html
Build with GCC compilers.
libmkl_intel_lp64.so =>
/usr/local_rwth/sw/python/2.7.12/x86_64/extra/lib/libmkl_intel_lp64.so
(0x00002abea70ad000)
libmkl_core.so =>
/usr/local_rwth/sw/python/2.7.12/x86_64/extra/lib/libmkl_core.so
(0x00002abea7bcb000)
libmkl_intel_thread.so =>
/usr/local_rwth/sw/python/2.7.12/x86_64/extra/lib/libmkl_intel_thread.so
(0x00002abea96ba000)
Using mkl_get_version_string() shows that the python mkl is version
2017.0.0 instead of the expected 2019.0.1 version that should be loaded.
A different approach to a hand-build module system would be using
easybuild to create the module system. This would avoid such issues.
The blue print paper can be found here:
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7830454
JSC has published there easybuild configuration on github:
https://github.com/easybuilders/JSC
The config files from HPC-UGent are also publicly available.
Best,
Sebastian
Hi all,
I have looked into the Network Performance on CLAIX18. I have measured
latency and bandwidth for intra and inter node communication. I have
used the Intel IMB PingPong Benchmark complied with the modules
intel/19.0 and intelmpi/2019. To get a sufficient statistic I have
submitted 64 jobs with 1 node using 2 tasks and 64 jobs with 2 nodes
using 1 task each, respectively. The scheduler has started the jobs on
different sets of nodes. I have attached the results, showing the
configuration and the average, min and max of the measurement.
Let's first look at the inter node communication: I have measured an
average latency of 2.12 usec. In the best case I measured 1 usec and in
the maximum is 7.1 usec. The bandwidth is on average 6488 Mbytes/sec.
The maximum is 11995 Mbytes/sec and minimum is 2483 Mbytes/sec.
The latency for intra node communication looks okay, however the
bandwidth shows variation.
On average theses results don't correspond with the advertised values
from Intel. Either I have done something wrong or I haven't understood
the topology or there is a problem with the machine.
Have you run such a benchmark as well? Can you observe something similar?
@Marcus: To get a better understanding of the machine, could you please
share a bit more information on the network topology:
- How many levels does the tree have?
- On which level is the tree pruned?
- Could you send me the connectivity file / connection map, e.g. a list
of cables connecting the nodes, edge and core switches? I would like to
add the hop count information into my result. (I have a script for
computing the hop count from a connection map. Depending on the format I
just need to adjust the reading routine)
Cheers,
Sebastian
