Hi Jodie,
what version of SLURM are you using? I'm pretty sure newer versions pick
the topology up automatically (although I'm on 18.08 so I can't verify
that).
Is what you're wanting to do - basically - forcefully feed a 'wrong'
gres.conf to make SLURM assume all GPUs are on one CPU? (I don't think
I've ever tried that!).
I have no idea, unfortunately, what CPU SLURM assigns first - it will
not (I don't think) assign cores on the non-GPU CPU first (other people
please correct me if I'm wrong!).
My gres.conf files get written by my config management from the GPU
topology, I don't think I've ever written one of them manually. And I've
never tried to make them anything wrong, i.e. I've never tried to
deliberately give a
The GRES conf would probably need to look something like
Name=gpu Type=tesla File=/dev/nvidia0 CPUs=0-13
Name=gpu Type=tesla File=/dev/nvidia1 CPUs=0-13
Name=gpu Type=tesla File=/dev/nvidia2 CPUs=0-13
Name=gpu Type=tesla File=/dev/nvidia3 CPUs=0-13
or maybe
Name=gpu Type=tesla File=/dev/nvidia0 CPUs=14-27
Name=gpu Type=tesla File=/dev/nvidia1 CPUs=14-27
Name=gpu Type=tesla File=/dev/nvidia2 CPUs=14-27
Name=gpu Type=tesla File=/dev/nvidia3 CPUs=14-27
to 'assign' all GPUs to the first 14 CPUs or second 14 CPUs (your config
makes me think there are two 14 core CPUs, so cores 0-13 would probably
be CPU1 etc?)
(What is the actual topology of the system (according to, say
'nvidia-smi topo -m')?)
Tina
On 07/08/2020 16:31, Jodie H. Sprouse wrote:
Tina,
Thank you. Yes, jobs will run on all 4 gpus if I submit with:
--gres-flags=disable-binding
Yet my goal is to have the gpus bind to a cpu in order to allow a cpu-only job
to never run on that particular cpu (having it bound to the gpu and always
free for a gpu job) and give the cpu job the maxcpus minus the 4.
* Hyperthreading is turned on.
NodeName=c000[1-5] Gres=gpu:tesla:4 Boards=1 SocketsPerBoard=2
CoresPerSocket=14 ThreadsPerCore=2 RealMemory=190000
PartitionName=gpu Nodes=c000[1-5] Default=NO DefaultTime=1:00:00 MaxTime=168:00:00
State=UP OverSubscribe=NO TRESBillingWeights="CPU=.25,Mem=0.25G,gres/gpu=2.0"
PartitionName=cpu Nodes=c000[1-5] Default=NO DefaultTime=1:00:00 MaxTime=168:00:00
State=UP OverSubscribe=NO TRESBillingWeights="CPU=.25,Mem=0.25G"
MaxCPUsPerNode=48
I have played tried variations for gres.conf such as:
NodeName=c0005 Name=gpu File=/dev/nvidia[0-1] CPUs=0,2
NodeName=c0005 Name=gpu File=/dev/nvidia[2-3] CPUs=1,3
as well as trying CORES= (rather than CPUSs) with NO success.
I’ve battled this all week. Any suggestions would be greatly appreciated!
Thanks for any suggestions!
Jodie
On Aug 7, 2020, at 11:12 AM, Tina Friedrich <tina.friedr...@it.ox.ac.uk> wrote:
Hello,
This is something I've seen once on our systems & it took me a while to figure
out what was going on.
The solution was that the system topology was such that all GPUs were connected
to one CPU. There were no free cores on that particular CPU; so SLURM did not
schedule any more jobs to the GPUs. Needed to disable binding in job submission
to schedule to all of them.
Not sure that applies in your situation (don't know your system), but it's
something to check?
Tina
On 07/08/2020 15:42, Jodie H. Sprouse wrote:
Good morning.
I have having the same experience here. Wondering if you had a resolution?
Thank you.
Jodie
On Jun 11, 2020, at 3:27 PM, Rhian Resnick <rresn...@fau.edu
<mailto:rresn...@fau.edu>> wrote:
We have several users submitting single GPU jobs to our cluster. We expected
the jobs to fill each node and fully utilize the available GPU's but we instead
find that only 2 out of the 4 gpu's in each node gets allocated.
If we request 2 GPU's in the job and start two jobs, both jobs will start on
the same node fully allocating the node. We are puzzled about is going on and
any hints are welcome.
Thanks for your help,
Rhian
*Example SBATCH Script*
#!/bin/bash
#SBATCH --job-name=test
#SBATCH --partition=longq7-mri
#SBATCH -N 1
#SBATCH -n 1
#SBATCH --gres=gpu:1
#SBATCH --mail-type=ALL
hostname
echo CUDA_VISIBLE_DEVICES $CUDA_VISIBLE_DEVICES
set | grep SLURM
nvidia-smi
sleep 500
*gres.conf*
#AutoDetect=nvml
Name=gpu Type=v100 File=/dev/nvidia0 Cores=0
Name=gpu Type=v100 File=/dev/nvidia1 Cores=1
Name=gpu Type=v100 File=/dev/nvidia2 Cores=2
Name=gpu Type=v100 File=/dev/nvidia3 Cores=3
*slurm.conf*
#
# Example slurm.conf file. Please run configurator.html
# (in doc/html) to build a configuration file customized
# for your environment.
#
#
# slurm.conf file generated by configurator.html.
#
# See the slurm.conf man page for more information.
#
ClusterName=cluster
ControlMachine=cluster-slurm1.example.com <http://cluster-slurm1.example.com/>
ControlAddr=10.116.0.11
BackupController=cluster-slurm2. <http://cluster-slurm2.example.com/>example.com
<http://cluster-slurm2.example.com/>
BackupAddr=10.116.0.17
#
SlurmUser=slurm
#SlurmdUser=root
SlurmctldPort=6817
SlurmdPort=6818
SchedulerPort=7321
RebootProgram="/usr/sbin/reboot"
AuthType=auth/munge
#JobCredentialPrivateKey=
#JobCredentialPublicCertificate=
StateSaveLocation=/var/spool/slurm/ctld
SlurmdSpoolDir=/var/spool/slurm/d
SwitchType=switch/none
MpiDefault=none
SlurmctldPidFile=/var/run/slurmctld.pid
SlurmdPidFile=/var/run/slurmd.pid
ProctrackType=proctrack/pgid
GresTypes=gpu,mps,bandwidth
PrologFlags=x11
#PluginDir=
#FirstJobId=
#MaxJobCount=
#PlugStackConfig=
#PropagatePrioProcess=
#PropagateResourceLimits=
#PropagateResourceLimitsExcept=
#Prolog=
#Epilog=/etc/slurm/slurm.epilog.clean
#SrunProlog=
#SrunEpilog=
#TaskProlog=
#TaskEpilog=
#TaskPlugin=
#TrackWCKey=no
#TreeWidth=50
#TmpFS=
#UsePAM=
#
# TIMERS
SlurmctldTimeout=300
SlurmdTimeout=300
InactiveLimit=0
MinJobAge=300
KillWait=30
Waittime=0
#
# SCHEDULING
SchedulerType=sched/backfill
#bf_interval=10
#SchedulerAuth=
#SelectType=select/linear
# Cores and memory are consumable
#SelectType=select/cons_res
#SelectTypeParameters=CR_Core_Memory
SchedulerParameters=bf_interval=10
SelectType=select/cons_res
SelectTypeParameters=CR_Core
FastSchedule=1
#PriorityType=priority/multifactor
#PriorityDecayHalfLife=14-0
#PriorityUsageResetPeriod=14-0
#PriorityWeightFairshare=100000
#PriorityWeightAge=1000
#PriorityWeightPartition=10000
#PriorityWeightJobSize=1000
#PriorityMaxAge=1-0
#
# LOGGING
SlurmctldDebug=3
SlurmctldLogFile=/var/log/slurmctld.log
SlurmdDebug=3
SlurmdLogFile=/var/log/slurmd.log
JobCompType=jobcomp/none
#JobCompLoc=
#
# ACCOUNTING
#JobAcctGatherType=jobacct_gather/linux
#JobAcctGatherFrequency=30
#
#AccountingStorageType=accounting_storage/slurmdbd
#AccountingStorageHost=
#AccountingStorageLoc=
#AccountingStoragePass=
#AccountingStorageUser=
#
#
#
# Default values
# DefMemPerNode=64000
# DefCpuPerGPU=4
# DefMemPerCPU=4000
# DefMemPerGPU=16000
# OpenHPC default configuration
#TaskPlugin=task/affinity
TaskPlugin=task/affinity,task/cgroup
PropagateResourceLimitsExcept=MEMLOCK
TaskPluginParam=autobind=cores
#AccountingStorageType=accounting_storage/mysql
#StorageLoc=slurm_acct_db
AccountingStorageType=accounting_storage/slurmdbd
AccountingStorageHost=cluster-slurmdbd1.example.com
<http://cluster-slurmdbd1.example.com/>
#AccountingStorageType=accounting_storage/filetxt
Epilog=/etc/slurm/slurm.epilog.clean
#PartitionName=normal Nodes=c[1-5] Default=YES MaxTime=24:00:00 State=UP
PartitionName=DEFAULT State=UP Default=NO AllowGroups=ALL Priority=10
DisableRootJobs=NO RootOnly=NO Hidden=NO Shared=NO GraceTime=0 PreemptMode=OFF
ReqResv=NO AllowAccounts=ALL AllowQos=ALL LLN=NO ExclusiveUser=NO
Nodes=nodeamd[009-016],c[1-4],nodehtc[001-025]
# Partitions
# Group Limited Queues
# OIT DEBUG QUEUE
PartitionName=debug Nodes=c[1-4] MaxTime=24:00:00 State=UP
AllowGroups=oit-hpc-admin
# RNA CHEM
PartitionName=longq7-rna MinNodes=1 MaxNodes=30 DefaultTime=168:00:00
MaxTime=UNLIMITED Priority=200 Nodes=nodeamd[001-008],nodegpu[021-025]
AllowGroups=gpu-rnachem
# V100's
PartitionName=longq7-mri MinNodes=1 MaxNodes=30 DefaultTime=168:00:00
MaxTime=168:00:00 Priority=200 Nodes=nodenviv100[001-016] AllowGroups=gpu-mri
# BIGDATA GRANT
PartitionName=longq-bigdata7 MinNodes=1 MaxNodes=30 DefaultTime=168:00:00
MaxTime=168:00:00 Priority=200 Nodes=node[087-098],nodegpu001
AllowGroups=fau-bigdata,nsf-bigdata
PartitionName=gpu-bigdata7 Default=NO MinNodes=1 Priority=10 AllowAccounts=ALL
Nodes=nodegpu001 AllowGroups=fau-bigdata,nsf-bigdata
# CogNeuroLab
PartitionName=CogNeuroLab Default=NO MinNodes=1 MaxNodes=4 MaxTime=7-12:00:00
AllowGroups=cogneurolab Priority=200 State=UP Nodes=node[001-004]
# Standard queues
# OPEN TO ALL
#Short Queue
PartitionName=shortq7 MinNodes=1 MaxNodes=30 DefaultTime=06:00:00
MaxTime=06:00:00 Priority=100
Nodes=nodeamd[001-016],nodenviv100[001-015],nodegpu[001-025],node[001-100],nodehtc[001-025]
Default=YES
# Medium Queue
PartitionName=mediumq7 MinNodes=1 MaxNodes=30 DefaultTime=72:00:00
MaxTime=72:00:00 Priority=50 Nodes=nodeamd[009-016],node[004-100]
# Long Queue
PartitionName=longq7 MinNodes=1 MaxNodes=30 DefaultTime=168:00:00
MaxTime=168:00:00 Priority=30 Nodes=nodeamd[009-016],node[004-100]
# Interactive
PartitionName=interactive MinNodes=1 MaxNodes=4 DefaultTime=06:00:00
MaxTime=06:00:00 Priority=101 Nodes=node[001-100] Default=No Hidden=YES
# Nodes
# Test nodes, (vms)
NodeName=c[1-4] Cpus=4 Feature=virtual RealMemory=16000
# AMD Nodes
NodeName=nodeamd[001-016] Procs=64 Boards=1 SocketsPerBoard=8 CoresPerSocket=8
ThreadsPerCore=1 Features=amd,epyc RealMemory=225436
# V100 MRI
NodeName=nodenviv100[001-016] CPUs=64 Boards=1 SocketsPerBoard=2
CoresPerSocket=16 ThreadsPerCore=2 Gres=gpu:v100:4 Feature=v100
RealMemory=192006
# GPU nodes
NodeName=nodegpu001 Procs=40 Boards=1 SocketsPerBoard=2 CoresPerSocket=10
ThreadsPerCore=2 Gres=gpu:k80:8 Feature=k80,intel RealMemory=64000
NodeName=nodegpu002 Procs=40 Boards=1 SocketsPerBoard=2 CoresPerSocket=10
ThreadsPerCore=2 Gres=gpu:gk1:8 Feature=gk1,intel RealMemory=128000
NodeName=nodegpu[003-020] Boards=1 SocketsPerBoard=2 CoresPerSocket=8
ThreadsPerCore=2 Gres=gpu:gk1:8 Feature=gk1,intel RealMemory=128000
NodeName=nodegpu[021-025] Procs=16 Boards=1 SocketsPerBoard=2 CoresPerSocket=8
ThreadsPerCore=1 Gres=gpu:4 Feature=exxact,intel RealMemory=128000
# IvyBridge nodes
NodeName=node[001-021] Procs=20 Boards=1 SocketsPerBoard=2 CoresPerSocket=10
ThreadsPerCore=1 Feature=intel,ivybridge RealMemory=112750
# SandyBridge node(2)
NodeName=node022 Procs=16 Boards=1 SocketsPerBoard=2 CoresPerSocket=8
ThreadsPerCore=1 Feature=intel,sandybridge RealMemory=64000
# IvyBridge
NodeName=node[023-050] Procs=20 Boards=1 SocketsPerBoard=2 CoresPerSocket=10
ThreadsPerCore=1 Feature=intel,ivybridge RealMemory=112750
# Haswell
NodeName=node[051-100] Procs=20 Boards=1 SocketsPerBoard=2 CoresPerSocket=10
ThreadsPerCore=1 Feature=intel,haswell RealMemory=112750
# Node health monitoring
HealthCheckProgram=/usr/sbin/nhc
HealthCheckInterval=300
ReturnToService=2
# Fix for X11 issues
X11Parameters=use_raw_hostname
Rhian Resnick
Associate Director Research Computing
Enterprise Systems
Office of Information Technology
Florida Atlantic University
777 Glades Road, CM22, Rm 173B
Boca Raton, FL 33431
Phone 561.297.2647
Fax 561.297.0222
