Slurm Pilot project for Biwi

• The following information is an abbreviated How-To with specific information for the pilot cluster

• Our official documentation for slurm is the Computing wiki article, you need to read this as well.

• Please bear in mind the final documentation is meant to be the above article. It will be extended with your feedback valid for all slurm users and a specific section or additional page concerning only Biwi.

• The goal of this pilot is to have a documentation to enable SGE users to migrate their jobs to Slurm. This also means the section Accouns and limits has only informative purpose at the moment.

The alpha version of a GPUMon alternative is available. Please don't send feedback yet, use it as it is.

Pilot-specific information

Involved machines are

• biwirender01 for CPU computing

• biwirender03 for GPU-computing

All available GPU partitions are overlayed on biwirender03. They will be available on different nodes in the final cluster.

long partitions are not yet implemented in the pilot!

Initialising slurm

All slurm command read the cluster configuration from the environment variable SLURM_CONF, so it needs to be set:

export SLURM_CONF=/home/sladmcvl/slurm/slurm.conf

If you're interested, feel free to have a look at the configuration, feedback is welcome!

Available partitions

The equivalent to SGE's queues is called partitions in slurm.
sinfo shows all available partitions:

sinfo

Only the interactive partition gpu.debug should be specified (see below). The scheduler decides in which partition to put a job based on the resources requested by it.

Interactive jobs

For testing purposes a job with an interactive session with 1 GPU can be started:

srun --time 10 --partition=gpu.debug --gres=gpu:1 --pty bash -i

• Such jobs are placed in gpu.debug by the scheduler

Allocating resources

GPUs

For a job to have access to a GPU, GPU resources need to be requested with the option --gres=gpu:<n>
Here's the sample job submission script primes_1GPU.sh requesting 1 GPU:

#!/bin/sh
#
#SBATCH  --mail-type=ALL
#SBATCH  --gres=gpu:1
#SBATCH  --output=log/%j.out
export LOGFILE=`pwd`/log/$SLURM_JOB_ID.out
# env | grep SLURM_ #Uncomment this line to show environment variables set by slurm for a job
#
# binary to execute
codebin/primes $1
echo ""
echo "Job statistics: "
sstat -j $SLURM_JOB_ID --format=JobID,AveVMSize%15,MaxRSS%15,AveCPU%15
echo ""
exit 0;

• Make sure the directory wherein to store logfiles exists before submitting a job.

• Please keep the environment variable LOGFILE, it is used in the scheduler's epilog script to append information to your logfile after your job ended (and therefore doesn't have access to $SLURM_JOB_ID anymore).

• slurm also sets CUDA_VISIBLE_DEVICES. See the section GPU jobs in the main slurm article.

• A job requesting more GPUs than allowed by the QOS of the users's account (see Accouns and limits) will stay in "PENDING" state.

Memory

If you omit the --mem option, the default of 30G/GPU memory and 3CPUs/GPU will be allocated to your job, which will make the scheduler choose gpu.medium.normal:

sbatch primes_1GPU.sh
sbatch: GRES requested     : gpu:1
sbatch: GPUs requested     : 1
sbatch: Requested Memory   : ---
sbatch: CPUs requested     : ---
sbatch: Your job is a gpu job.
Submitted batch job 133

squeue --Format jobarrayid:8,partition:20,reasonlist:20,username:10,tres-alloc:45,timeused:10

JOBID   PARTITION           NODELIST(REASON)    USER      TRES_ALLOC                                   TIME
133     gpu.medium.normal   biwirender03        testuser  cpu=3,mem=30G,node=1,billing=3,gres/gpu=1    0:02

An explicit --mem option selects the partition as follows:

For example with:

sbatch --mem=50G primes_2GPU.sh

the above squeue command shows:

JOBID   PARTITION           NODELIST(REASON)    USER      TRES_ALLOC                                   TIME
136     gpu.high.normal     biwirender03        testuser  cpu=6,mem=100G,node=1,billing=6,gres/gpu=2   0:28

Accounts and limits

In slurm lingo an account is equivalent to a user group. The following accounts are configured for users to be added to:

sacctmgr show account

• Accounts isg and root are not accessible to Biwi

GPU limits are stored in so-called QOS, each account is associated with the QOS we want to apply to it. Limits apply to all users added to an account.

sacctmgr show assoc format=account%15,user%15,partition%15,maxjobs%8,qos%15,defaultqos%15

The QOS' gpu_x only contain a limit for the amount of GPUs per user:

sacctmgr show qos format=name%15,maxtrespu%30

Users with administrative privileges can move a user between accounts deadline or deadconf.

List associations of testuser:

sacctmgr show assoc where user=testuser format=account%15,user%15,partition%15,maxjobs%8,qos%15,defaultqos%15

        Account            User       Partition  MaxJobs             QOS         Def QOS
--------------- --------------- --------------- -------- --------------- ---------------
       deadline        testuser                                    gpu_3           gpu_3

Move testuser from deadline to staff:

/home/sladmcvl/slurm/change_account_of_user.sh testuser deadline staff

List associations of testuser again:

sacctmgr show assoc where user=testuser format=account%15,user%15,partition%15,maxjobs%8,qos%15,defaultqos%15

        Account            User       Partition  MaxJobs             QOS         Def QOS
--------------- --------------- --------------- -------- --------------- ---------------
          staff        testuser                                    gpu_2           gpu_2

Accounts with administrative privileges can be shown with:

sacctmgr show user format=user%15,defaultaccount%15,admin%15'

Last words

Have fun using SLURM for your jobs!

Content for the final page

Here starts the content which will eventually evolve into the final wiki page. The information won't be available all at once, it is an ongoing process.

Nodes

The following tables summarizes node specific information:

Detailled information about all nodes can be seen by issuing the command

scontrol show nodes

An overview of utilization of individual node's resources can be shown with:

sinfo --Format nodehost:14,statecompact:7,cpusstate:16,cpusload:11,memory:8,allocmem:10,gres:55,gresused:62,reason:10

(Adapt the field length for gres and gresused to your needs)

Partitions

Partitions including their limits are shown in the following table:

Def: Default, Max: Maximum, MPG: Memory Per GPU, CPG: CPUs Per GPU

gpu.debug

This partition is reserved to run interactive jobs for debugging purposes. If a job doesn't run a process on an allocated GPU after 20 minutes it will be killed.

*.long

The *.long partitions are only accessible to members of the account "long". Membership is temporary and granted on demand by <contact to be filled in>.

Display specific information

The following is a collection of command sequences to quickly extract specific summaries.

GPUs per user

Show a sorted list of users and a summary of the GPU's used by their jobs:

scontrol -a show jobs \
    |grep -E '(UserId|TRES)=' \
    |paste - - \
    |grep 'gres/gpu' \
    |sed -E 's:^\s+UserId=([^\(]+).*gres/gpu=([0-9]+)$:\1;\2:' \
    |awk -F ';' -v OFS=';' '{a[$1]+=$2}END{for(i in a) print i,a[i]}' \
    |sort