Cluster Cosmology

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h1. Hardware overview

You access the Euclid cluster through alexandria@usm.uni-muenchen.de

* alexandria is the file server and should not be used for computing

* There are 12 compute nodes named euclides1--euclides12

* euclides8 hosts a virtual machine and is not available for computing

* euclides12 is only available for debugging, see below

* euclides11 is currently used to test a different OS

* each node has 32 logical CPUs and 64GB of RAM

h1. How to run jobs on the euclides nodes (using Slurm)

Use slurm to submit jobs or login to the euclides nodes (euclides1-12).

*Please read through this entire wikipage so everyone can make efficient use of this cluster*

h2. alexandria

*Please do not use alexandria as a compute node* - it's hardware is different from the nodes. It hosts our file server and other services that are important to us. 

You should use alexandria to

* transfer files

* compile your code

* submit jobs to the nodes

If you need to debug and would like to login to a node, please start an interactive job to one of the nodes using slurm. For instructions see below.

h2. euclides nodes

Job submission to the euclides nodes is handled by the slurm jobmanager (see http://slurm.schedmd.com and https://computing.llnl.gov/linux/slurm/). 

*Important: In order to run jobs, you need to be added to the slurm accounting system - please contact the admin*

All slurm commands listed below have very helpful man pages (e.g. man slurm, man squeue, ...). 

If you are already familiar with another jobmanager the following information may be helpful to you http://slurm.schedmd.com/rosetta.pdf‎.

h3. Scheduling of Jobs

At this point there are two queues, called partitions in slurm: 

* *normal* which is the default partition your jobs will be sent to if you do not specify it otherwise. At this point there is a time limit of

two days. Jobs at this point can only run on 1 node.

* *debug* which is meant for debugging, you can only run one job at a time, other jobs submitted will remain in the queue. Time limit is

12 hours.

The default memory per core used is 2GB, if you need more or less, please specify with the --mem or --mem-per-cpu option.

We have also set up a scheduler that goes beyond the first come first serve - some jobs will be favoured over others depending

on how much you or your group have been using euclides in the past 2 weeks, how long the job has been queued and how much

resources it will consume.

This is serves as a starting point, we may have to adjust parameters once the slurm jobmanager is used. Job scheduling is a complex

issue and we still need to build expertise and gain experience what are the user needs in our groups. Please feel free to speak out if

there is something that can be improved without creating an unfair disadvantage for other users.

You can run interactive jobs on both partitions.

h3. Running an interactive job with slurm (a.k.a. logging in)

To run an interactive job with slurm in the default partition, use

<pre>

srun -u --pty bash

</pre>

If you want to use tcsh use

<pre>

srun -u --pty tcsh

</pre>

If you want to use a larger memory per job do

<pre>

srun -u --mem-per-cpu=8000 --pty tcsh

</pre>

In case you want to open x11 applications, use the --x11=first option, e.g.

<pre>

srun --x11=first -u   --pty  bash

</pre>

In case the 'normal' partition is overcrowded, to use the 'debug' partition, use:

<pre>

srun --account cosmo_debug -p debug -u --pty bash # if you are part of the Cosmology group

srun --account euclid_debug -p debug -u --pty bash  # if you are part of the EuclidDM group

</pre> As soon as a slot is open, slurm will log you in to an interactive session on one of the nodes.

h3. limited ssh access

If you have an active job (batch or interactive), you can login to the node the job is running on. Your ssh session will be killed if the job terminates. Your ssh session will be restricted to the same resources as your job (so you cannot accidentally bypass the job scheduler and harm other user's jobs).

h3. Running a simple once core batch job with slurm using the default partition

* To see what queues are available to you (called partitions in slurm), run:

<pre>

sinfo

</pre>

* To run slurm, create a myjob.slurm containing the following information:

<pre>

#!/bin/bash

#SBATCH --output=slurm.out

#SBATCH --error=slurm.err

#SBATCH --mail-user <put your email address here>

#SBATCH --mail-type=BEGIN

#SBATCH -p normal

/bin/hostname

</pre>

* To submit a batch job use:

<pre>

sbatch myjob.slurm

</pre>

* To see the status of you job, use 

<pre>

squeue

</pre>

* To kill a job use:

<pre>

scancel <jobid>

</pre> the <jobid> you can get from using squeue.

* For some more information on your job use

<pre>

scontrol show job <jobid>

</pre>the <jobid> you can get from using squeue.

h3. Running a simple once core batch job with slurm using the debug partition

Change the partition to debug and add the appropriate account depending if you're part of

the euclid or cosmology group.

<pre>

#!/bin/bash

#SBATCH --output=slurm.out

#SBATCH --error=slurm.err

#SBATCH --mail-user <put your email address here>

#SBATCH --mail-type=BEGIN

#SBATCH --account [cosmo_debug/euclid_debug]

#SBATCH -p debug

/bin/hostname

</pre>

h3. Accessing a node where a job is running or starting additional processes on a node

You can attach an srun command to an already existing job (batch or interactive). This

means you can start an interactive session on a node where a job of yours is running

or start an additional process.

First determine the jobid of the desired job using squeue, then use 

<pre>

srun  --jobid <jobid> [options] <executable> 

</pre>

Or more concrete

<pre>

srun  --jobid <jobid> -u --pty  bash # to start an interactive session

srun  --jobid <jobid> ps -eaFAl  # to start get detailed process information 

</pre>

The processes will only run on cores that have been allocated to you. This works 

for batch as well as interactive jobs. 

*Important: If the original job that was submitted is finished, any process 

attached in this fashion will be killed.*

h3. Batch script for running a multi-core job

mpi is installed on alexandria.

To run a 4 core job for an executable compiled with mpi you can use

<pre>

#!/bin/bash

#SBATCH --output=slurm.out

#SBATCH --error=slurm.err

#SBATCH --mail-user <put your email address here>

#SBATCH --mail-type=BEGIN

#SBATCH -n 4

mpirun <programname>

</pre>

and it will automatically start on the number of nodes specified.

To ensure that the job is being executed on only one node, add

<pre>

#SBATCH -n 4

</pre>

to the job script.

If you would like to run a program that itself starts processes, you can use the

environment variable $SLURM_NPROCS that is automatically defined for slurm

jobs to explicitly pass the number of cores the program can run on.

To check if your job is acutally running on the specified number of cores, you can check

the PSR column of

<pre>

ps -eaFAl

# or ps -eaFAl | egrep "<yourusername>|UID" if you just want to see your jobs

</pre>

h3. environment for jobs

By default, slurm does not initialize the environment (using .bashrc, .profile, .tcshrc, ...)

To use your usual system environment, add the following line in the submission script:

<pre>

#SBATCH --get-user-env

</pre>

h2. desdb node

Some specific jobs in cosmodb, such as the "catalog ingest", need to be performed on the machines desdb1/2. For those jobs there is the slurm account "euclid_cat_ing" with the partition "cat_ing". Only selected persons from the Euclid group have access to this node. Please specify "-p cat_ing" and "--account euclid_cat_ing" on the command line or in the slurm script.

h2. Software specific setup

h3. Python environment 

You can use the python 2.7.3 installed on the euclides cluster by using

<pre>

source /data2/users/ccsoft/etc/setup_all

source  /data2/users/ccsoft/etc/setup_python2.7.3

</pre>

h2. Notes For Euclid users

For those submitting jobs to euclides* nodes through Cosmo DM pipeline  here are some things which need to be specified for customized job submissions,

since a different interface to slurm is used.

* To use larger memory per block , specify max_memory = 6000 (for 6G) and so on. inside block definition or in the submit file (in

case you want to use it for all blocks)

* If you want to run on multiple cores/cores then use 

nodes='<number of nodes>:ppn=<number of cores> inside the block definition of a particular block or in the submit file in case you want

to use it for all blocks.

* If you want to use a larger wall time then specify wall_mod=<wall time in minutes> inside the module definition

* note that queue=serial does not work on alexandria(we usually use it for c2pap)

h1. Admin

There is a user "slurm" which however is not really necessary for the administration work. The slurm administrator needs sudo access. Some script for adding a user and similar things are in "/data1/users/slurm". With the sudo access the admin can execute those scripts. In the mysql database there is the username "slurmdb" with password.

h2. Overview over users, accounts, etc.

No sudo access needed:

<pre>

/usr/local/bin/sacctmgr show account withassoc

</pre>

h2. Adding a new user

As root on @alexandria@,

<pre>

cd /data1/users/slurm/

./add_user.sh UserName account(cosmo or euclid)

/usr/local/bin/.scontrol reconfigure

</pre>

h2. To increase memory, cores etc for a user

Inside script above, various commands for changing user settings, e.g.

<pre>

/usr/local/bin/sacctmgr -i modify user  name=$1 set GrpCPUs=32

/usr/local/bin/sacctmgr -i modify user  name=$1 set GrpMem=128000

</pre>

h2. Node state "drain"

When a node is in "drain" state when calling <pre>sinfo</pre>

run

<pre>

/usr/local/bin/scontrol update nodename=NODE_NAME state=resume

</pre>

to put it back to operation.

h2. Nodes down

Sometimes nodes are reported as "down". This seems to happen as a result of network problems. Here is some "troubleshooting":https://computing.llnl.gov/linux/slurm/troubleshoot.html#nodes for this situation. Also after a re-boot of alexandria some manual work on slurm might be necessary to get going again.