Revision 9 as of 2020-06-22 18:51:19

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Slurm Pilot project for Biwi

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

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

PARTITION         AVAIL  TIMELIMIT  NODES   STATE NODELIST
cpu.medium.normal    up 2-00:00:00      1   idle biwirender01
gpu.low.normal       up 2-00:00:00      1   idle biwirender03
gpu.medium.normal    up 2-00:00:00      1   idle biwirender03
gpu.medium.long      up 5-00:00:00      1   idle biwirender03
gpu.high.normal      up 2-00:00:00      1   idle biwirender03
gpu.high.long        up 5-00:00:00      1   idle biwirender03
gpu.debug            up    6:00:00      1   idle biwirender03
gpu.mon              up    6:00:00      1   idle biwirender03

Only interactive partitions gpu.debug and gpu.monitor can and 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

To monitor a running job, an interactive session can be started with explicitly selecting the monitoring partition. The node where the batch job is running needs to be specified as well:

srun --time 10 --partition=gpu.mon --nodelist=biwirender03 --pty bash -i

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:

#
#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;

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:

--mem

Partition

< 30G

gpu.low.normal

30G - 50G

gpu.medium.normal

>50G - 70G

gpu.high.normal

>70G

not allowed

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

   Account                Descr                  Org
---------- -------------------- --------------------
  deadconf  deadline_conference                 biwi
  deadline             deadline                 biwi
       isg                  isg                  isg
      root default root account                 root
     staff                staff                 biwi
   student              student                 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

        Account            User       Partition  MaxJobs             QOS         Def QOS
--------------- --------------- --------------- -------- --------------- ---------------
           root                                                   normal
           root            root                                   normal
       deadconf                                                    gpu_4           gpu_4
       deadline                                                    gpu_3           gpu_3
       deadline        ........                                    gpu_3           gpu_3
            isg                                                   normal
            isg        sladmall                                   normal
          staff                                                    gpu_2           gpu_2
          staff        ........                                    gpu_2           gpu_2
          staff        ........                                    gpu_2           gpu_2
          staff        ........                                    gpu_2           gpu_2
          staff        ........                                    gpu_2           gpu_2
          staff        ........                                    gpu_2           gpu_2
        student                                                    gpu_1           gpu_1

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

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

          Name                      MaxTRESPU
--------------- ------------------------------
         normal
          gpu_1                     gres/gpu=1
          gpu_2                     gres/gpu=2
          gpu_3                     gres/gpu=3
          gpu_4                     gres/gpu=4
          gpu_5                     gres/gpu=5
          gpu_6                     gres/gpu=6

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:

Server

CPU

Frequency

Cores

Memory

/scratch SSD

GPUs

Operating System

biwirender03

Intel Xeon E5-2650 v2

2.60 GHz

32

125 GB

-

6 Tesla K40c (11 GB)

Debian 9

biwirender04

Intel Xeon E5-2637 v2

3.50 GHz

8

125 GB

5 Tesla K40c (11 GB)

Debian 9

biwirender0[5,6]

Intel Xeon E5-2637 v2

3.50 GHz

8

251 GB

5 GeForce GTX TITAN X (12 GB)

Debian 9

biwirender0[7-9]

Intel Xeon E5-2640 v3

2.60 GHz

16

251 GB

5 GeForce GTX TITAN X (12 GB)

Debian 9

biwirender10

Intel Xeon E5-2650 v4

2.20 GHz

24

251 GB

5 GeForce GTX TITAN X (12 GB)

Debian 9

biwirender11

Intel Xeon E5-2640 v3

2.60 GHz

16

251 GB

5 GeForce GTX TITAN X (12 GB)

Debian 9

biwirender12

Intel Xeon E5-2640 v3

2.60 GHz

32

251 GB

6 GeForce RTX 2080 Ti (10 GB)

Debian 9

biwirender13

Intel Xeon E5-2680 v3

2.50 GHz

24

503 GB

4 TITAN Xp (12 GB)
3 TITAN Xp COLLECTORS EDITION (12 GB)

Debian 9

biwirender14

Intel Xeon E5-2680 v4

2.40 GHz

28

503 GB

3 TITAN Xp (12 GB)
4 TITAN Xp COLLECTORS EDITION (12 GB)

Debian 9

biwirender15

Intel Xeon E5-2680 v4

2.40 GHz

28

503 GB

3 TITAN Xp (12 GB)
3 TITAN Xp COLLECTORS EDITION (12 GB)

Debian 9

biwirender17

Intel Xeon E5-2620 v4

2.10 GHz

32

503 GB

8 GeForce GTX 1080 Ti (11 GB)

Debian 9

biwirender20

Intel Xeon E5-2620 v4

2.10 GHz

32

377 GB

8 GeForce GTX 1080 Ti (11 GB)

Debian 9

bmicgpu01

Intel Xeon E5-2680 v3

2.50 GHz

24

251 GB

6 TITAN X (Pascal) (12 GB)

Debian 9

bmicgpu02

Intel Xeon E5-2640 v3

2.60 GHz

16

251 GB

5 TITAN Xp (12 GB)

Debian 9

bmicgpu0[3-5]

Intel Xeon E5-2630 v4

2.20 GHz

20

251 GB

6 TITAN Xp (12 GB)

Debian 9

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:12,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:

Partition

DefMPG

MaxMPG

DefCPG

MaxCPG

Time limit

cpu.medium.normal

-

-

-

-

2 d

gpu.low.normal

20 GB

25 GB

3

3

2 d

gpu.medium.normal

40 GB

50 GB

3

5

2 d

gpu.medium.long

40 GB

50 GB

3

5

5 d

gpu.high.normal

70 GB

70 GB

4

4

2 d

gpu.high.long

70 GB

70 GB

4

4

5 d

gpu.debug

20 GB

25 GB

3

3

8 h

gpu.mon

-

-

-

-

15 m

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.

gpu.mon

This partition is reserved to run interactive jobs for monitoring other running jobs. No GPUs can be allocated, only 1 core per job and 1 job per person is allowed.

/!\ This might be replaced by an explanation how to reserve a job step in a job for monitoring and attach to such a job ste.

*.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>.