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srun and openmpi not launching parallel jobs


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I can't seem to run MPI jobs using slurm. Any help or advice?



Running a local home based mini cluster to use all of my processors. I'm using 18.04, and have installed the stock openmpi and slurm packages. I have a small test program that I use to show which cores I'm running on. When I run with mpirun I get:



$ mpirun -N 3 MPI_Hello
Process 1 on ubuntu18.davidcarter.ca, out of 3
Process 2 on ubuntu18.davidcarter.ca, out of 3
Process 0 on ubuntu18.davidcarter.ca, out of 3


When I run with srun I get:



$ srun -n 3 MPI_Hello
Process 0 on ubuntu18.davidcarter.ca, out of 1
Process 0 on ubuntu18.davidcarter.ca, out of 1
Process 0 on ubuntu18.davidcarter.ca, out of 1


I've done this many times with different arguments (--mpi=pmi2, --mpi=openmpi, etc) and can confirm that instead of running a job with n parallel threads it runs n single threaded jobs. n times the work with 1/n times the expected resources per job.



This is my test program:



#include <stdio.h>
#include <mpi.h>

int main(int argc, char** argv) {
int numprocs, rank, namelen;
char processor_name[MPI_MAX_PROCESSOR_NAME];

MPI_Init (&argc, &argv);
MPI_Comm_size(MPI_COMM_WORLD, &numprocs);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Get_processor_name(processor_name, &namelen);

printf("Process %d on %s, out of %dn", rank, processor_name, numprocs);

MPI_Finalize();
}


This is my /etc/slurm-llnl/slurm.conf:



# slurm.conf file generated by configurator easy.html.
# Put this file on all nodes of your cluster.
# See the slurm.conf man page for more information.
#
ControlMachine=ubuntu18.davidcarter.ca
#ControlAddr=
#
#MailProg=/bin/mail
MpiDefault=none
MpiParams=ports=12000-12100
ProctrackType=proctrack/pgid
ReturnToService=1
SlurmctldPidFile=/var/run/slurm-llnl/slurmctld.pid
#SlurmctldPort=6817
SlurmdPidFile=/var/run/slurm-llnl/slurmd.pid
#SlurmdPort=6818
SlurmdSpoolDir=/var/lib/slurm-llnl/slurmd
SlurmUser=slurm
#SlurmdUser=root
StateSaveLocation=/var/lib/slurm-llnl/slurmctld
SwitchType=switch/none
TaskPlugin=task/affinity
#
#
# TIMERS
#KillWait=30
#MinJobAge=300
#SlurmctldTimeout=120
#SlurmdTimeout=300
#
#
# SCHEDULING
FastSchedule=1
SchedulerType=sched/backfill
#SchedulerPort=7321
SelectType=select/linear
#
#
# LOGGING AND ACCOUNTING
AccountingStorageType=accounting_storage/none
ClusterName=cluster
#JobAcctGatherFrequency=30
JobAcctGatherType=jobacct_gather/linux
#SlurmctldDebug=3
SlurmctldLogFile=/var/log/slurm-llnl/slurmctld.log
#SlurmdDebug=3
SlurmdLogFile=/var/log/slurm-llnl/slurmd.log
#
#
# COMPUTE NODES
#NodeName=compute[1-4] Sockets=1 CoresPerSocket=2 RealMemory=1900 State=UNKNOWN
#NodeName=compute[1-2] Sockets=1 CoresPerSocket=4 RealMemory=3800 State=UNKNOWN
NodeName=compute1 Sockets=8 CoresPerSocket=1 RealMemory=7900 State=UNKNOWN
NodeName=ubuntu18 Sockets=1 CoresPerSocket=3 RealMemory=7900 State=UNKNOWN

#
# Partitions
PartitionName=debug Nodes=ubuntu18 Default=YES MaxTime=INFINITE State=UP OverSubscribe=NO
PartitionName=batch Nodes=compute1 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO
PartitionName=prod Nodes=compute1,ubuntu18 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO








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    I can't seem to run MPI jobs using slurm. Any help or advice?



    Running a local home based mini cluster to use all of my processors. I'm using 18.04, and have installed the stock openmpi and slurm packages. I have a small test program that I use to show which cores I'm running on. When I run with mpirun I get:



    $ mpirun -N 3 MPI_Hello
    Process 1 on ubuntu18.davidcarter.ca, out of 3
    Process 2 on ubuntu18.davidcarter.ca, out of 3
    Process 0 on ubuntu18.davidcarter.ca, out of 3


    When I run with srun I get:



    $ srun -n 3 MPI_Hello
    Process 0 on ubuntu18.davidcarter.ca, out of 1
    Process 0 on ubuntu18.davidcarter.ca, out of 1
    Process 0 on ubuntu18.davidcarter.ca, out of 1


    I've done this many times with different arguments (--mpi=pmi2, --mpi=openmpi, etc) and can confirm that instead of running a job with n parallel threads it runs n single threaded jobs. n times the work with 1/n times the expected resources per job.



    This is my test program:



    #include <stdio.h>
    #include <mpi.h>

    int main(int argc, char** argv) {
    int numprocs, rank, namelen;
    char processor_name[MPI_MAX_PROCESSOR_NAME];

    MPI_Init (&argc, &argv);
    MPI_Comm_size(MPI_COMM_WORLD, &numprocs);
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);
    MPI_Get_processor_name(processor_name, &namelen);

    printf("Process %d on %s, out of %dn", rank, processor_name, numprocs);

    MPI_Finalize();
    }


    This is my /etc/slurm-llnl/slurm.conf:



    # slurm.conf file generated by configurator easy.html.
    # Put this file on all nodes of your cluster.
    # See the slurm.conf man page for more information.
    #
    ControlMachine=ubuntu18.davidcarter.ca
    #ControlAddr=
    #
    #MailProg=/bin/mail
    MpiDefault=none
    MpiParams=ports=12000-12100
    ProctrackType=proctrack/pgid
    ReturnToService=1
    SlurmctldPidFile=/var/run/slurm-llnl/slurmctld.pid
    #SlurmctldPort=6817
    SlurmdPidFile=/var/run/slurm-llnl/slurmd.pid
    #SlurmdPort=6818
    SlurmdSpoolDir=/var/lib/slurm-llnl/slurmd
    SlurmUser=slurm
    #SlurmdUser=root
    StateSaveLocation=/var/lib/slurm-llnl/slurmctld
    SwitchType=switch/none
    TaskPlugin=task/affinity
    #
    #
    # TIMERS
    #KillWait=30
    #MinJobAge=300
    #SlurmctldTimeout=120
    #SlurmdTimeout=300
    #
    #
    # SCHEDULING
    FastSchedule=1
    SchedulerType=sched/backfill
    #SchedulerPort=7321
    SelectType=select/linear
    #
    #
    # LOGGING AND ACCOUNTING
    AccountingStorageType=accounting_storage/none
    ClusterName=cluster
    #JobAcctGatherFrequency=30
    JobAcctGatherType=jobacct_gather/linux
    #SlurmctldDebug=3
    SlurmctldLogFile=/var/log/slurm-llnl/slurmctld.log
    #SlurmdDebug=3
    SlurmdLogFile=/var/log/slurm-llnl/slurmd.log
    #
    #
    # COMPUTE NODES
    #NodeName=compute[1-4] Sockets=1 CoresPerSocket=2 RealMemory=1900 State=UNKNOWN
    #NodeName=compute[1-2] Sockets=1 CoresPerSocket=4 RealMemory=3800 State=UNKNOWN
    NodeName=compute1 Sockets=8 CoresPerSocket=1 RealMemory=7900 State=UNKNOWN
    NodeName=ubuntu18 Sockets=1 CoresPerSocket=3 RealMemory=7900 State=UNKNOWN

    #
    # Partitions
    PartitionName=debug Nodes=ubuntu18 Default=YES MaxTime=INFINITE State=UP OverSubscribe=NO
    PartitionName=batch Nodes=compute1 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO
    PartitionName=prod Nodes=compute1,ubuntu18 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO








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    David Carter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      0












      0








      0








      I can't seem to run MPI jobs using slurm. Any help or advice?



      Running a local home based mini cluster to use all of my processors. I'm using 18.04, and have installed the stock openmpi and slurm packages. I have a small test program that I use to show which cores I'm running on. When I run with mpirun I get:



      $ mpirun -N 3 MPI_Hello
      Process 1 on ubuntu18.davidcarter.ca, out of 3
      Process 2 on ubuntu18.davidcarter.ca, out of 3
      Process 0 on ubuntu18.davidcarter.ca, out of 3


      When I run with srun I get:



      $ srun -n 3 MPI_Hello
      Process 0 on ubuntu18.davidcarter.ca, out of 1
      Process 0 on ubuntu18.davidcarter.ca, out of 1
      Process 0 on ubuntu18.davidcarter.ca, out of 1


      I've done this many times with different arguments (--mpi=pmi2, --mpi=openmpi, etc) and can confirm that instead of running a job with n parallel threads it runs n single threaded jobs. n times the work with 1/n times the expected resources per job.



      This is my test program:



      #include <stdio.h>
      #include <mpi.h>

      int main(int argc, char** argv) {
      int numprocs, rank, namelen;
      char processor_name[MPI_MAX_PROCESSOR_NAME];

      MPI_Init (&argc, &argv);
      MPI_Comm_size(MPI_COMM_WORLD, &numprocs);
      MPI_Comm_rank(MPI_COMM_WORLD, &rank);
      MPI_Get_processor_name(processor_name, &namelen);

      printf("Process %d on %s, out of %dn", rank, processor_name, numprocs);

      MPI_Finalize();
      }


      This is my /etc/slurm-llnl/slurm.conf:



      # slurm.conf file generated by configurator easy.html.
      # Put this file on all nodes of your cluster.
      # See the slurm.conf man page for more information.
      #
      ControlMachine=ubuntu18.davidcarter.ca
      #ControlAddr=
      #
      #MailProg=/bin/mail
      MpiDefault=none
      MpiParams=ports=12000-12100
      ProctrackType=proctrack/pgid
      ReturnToService=1
      SlurmctldPidFile=/var/run/slurm-llnl/slurmctld.pid
      #SlurmctldPort=6817
      SlurmdPidFile=/var/run/slurm-llnl/slurmd.pid
      #SlurmdPort=6818
      SlurmdSpoolDir=/var/lib/slurm-llnl/slurmd
      SlurmUser=slurm
      #SlurmdUser=root
      StateSaveLocation=/var/lib/slurm-llnl/slurmctld
      SwitchType=switch/none
      TaskPlugin=task/affinity
      #
      #
      # TIMERS
      #KillWait=30
      #MinJobAge=300
      #SlurmctldTimeout=120
      #SlurmdTimeout=300
      #
      #
      # SCHEDULING
      FastSchedule=1
      SchedulerType=sched/backfill
      #SchedulerPort=7321
      SelectType=select/linear
      #
      #
      # LOGGING AND ACCOUNTING
      AccountingStorageType=accounting_storage/none
      ClusterName=cluster
      #JobAcctGatherFrequency=30
      JobAcctGatherType=jobacct_gather/linux
      #SlurmctldDebug=3
      SlurmctldLogFile=/var/log/slurm-llnl/slurmctld.log
      #SlurmdDebug=3
      SlurmdLogFile=/var/log/slurm-llnl/slurmd.log
      #
      #
      # COMPUTE NODES
      #NodeName=compute[1-4] Sockets=1 CoresPerSocket=2 RealMemory=1900 State=UNKNOWN
      #NodeName=compute[1-2] Sockets=1 CoresPerSocket=4 RealMemory=3800 State=UNKNOWN
      NodeName=compute1 Sockets=8 CoresPerSocket=1 RealMemory=7900 State=UNKNOWN
      NodeName=ubuntu18 Sockets=1 CoresPerSocket=3 RealMemory=7900 State=UNKNOWN

      #
      # Partitions
      PartitionName=debug Nodes=ubuntu18 Default=YES MaxTime=INFINITE State=UP OverSubscribe=NO
      PartitionName=batch Nodes=compute1 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO
      PartitionName=prod Nodes=compute1,ubuntu18 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO








      share







      New contributor




      David Carter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.












      I can't seem to run MPI jobs using slurm. Any help or advice?



      Running a local home based mini cluster to use all of my processors. I'm using 18.04, and have installed the stock openmpi and slurm packages. I have a small test program that I use to show which cores I'm running on. When I run with mpirun I get:



      $ mpirun -N 3 MPI_Hello
      Process 1 on ubuntu18.davidcarter.ca, out of 3
      Process 2 on ubuntu18.davidcarter.ca, out of 3
      Process 0 on ubuntu18.davidcarter.ca, out of 3


      When I run with srun I get:



      $ srun -n 3 MPI_Hello
      Process 0 on ubuntu18.davidcarter.ca, out of 1
      Process 0 on ubuntu18.davidcarter.ca, out of 1
      Process 0 on ubuntu18.davidcarter.ca, out of 1


      I've done this many times with different arguments (--mpi=pmi2, --mpi=openmpi, etc) and can confirm that instead of running a job with n parallel threads it runs n single threaded jobs. n times the work with 1/n times the expected resources per job.



      This is my test program:



      #include <stdio.h>
      #include <mpi.h>

      int main(int argc, char** argv) {
      int numprocs, rank, namelen;
      char processor_name[MPI_MAX_PROCESSOR_NAME];

      MPI_Init (&argc, &argv);
      MPI_Comm_size(MPI_COMM_WORLD, &numprocs);
      MPI_Comm_rank(MPI_COMM_WORLD, &rank);
      MPI_Get_processor_name(processor_name, &namelen);

      printf("Process %d on %s, out of %dn", rank, processor_name, numprocs);

      MPI_Finalize();
      }


      This is my /etc/slurm-llnl/slurm.conf:



      # slurm.conf file generated by configurator easy.html.
      # Put this file on all nodes of your cluster.
      # See the slurm.conf man page for more information.
      #
      ControlMachine=ubuntu18.davidcarter.ca
      #ControlAddr=
      #
      #MailProg=/bin/mail
      MpiDefault=none
      MpiParams=ports=12000-12100
      ProctrackType=proctrack/pgid
      ReturnToService=1
      SlurmctldPidFile=/var/run/slurm-llnl/slurmctld.pid
      #SlurmctldPort=6817
      SlurmdPidFile=/var/run/slurm-llnl/slurmd.pid
      #SlurmdPort=6818
      SlurmdSpoolDir=/var/lib/slurm-llnl/slurmd
      SlurmUser=slurm
      #SlurmdUser=root
      StateSaveLocation=/var/lib/slurm-llnl/slurmctld
      SwitchType=switch/none
      TaskPlugin=task/affinity
      #
      #
      # TIMERS
      #KillWait=30
      #MinJobAge=300
      #SlurmctldTimeout=120
      #SlurmdTimeout=300
      #
      #
      # SCHEDULING
      FastSchedule=1
      SchedulerType=sched/backfill
      #SchedulerPort=7321
      SelectType=select/linear
      #
      #
      # LOGGING AND ACCOUNTING
      AccountingStorageType=accounting_storage/none
      ClusterName=cluster
      #JobAcctGatherFrequency=30
      JobAcctGatherType=jobacct_gather/linux
      #SlurmctldDebug=3
      SlurmctldLogFile=/var/log/slurm-llnl/slurmctld.log
      #SlurmdDebug=3
      SlurmdLogFile=/var/log/slurm-llnl/slurmd.log
      #
      #
      # COMPUTE NODES
      #NodeName=compute[1-4] Sockets=1 CoresPerSocket=2 RealMemory=1900 State=UNKNOWN
      #NodeName=compute[1-2] Sockets=1 CoresPerSocket=4 RealMemory=3800 State=UNKNOWN
      NodeName=compute1 Sockets=8 CoresPerSocket=1 RealMemory=7900 State=UNKNOWN
      NodeName=ubuntu18 Sockets=1 CoresPerSocket=3 RealMemory=7900 State=UNKNOWN

      #
      # Partitions
      PartitionName=debug Nodes=ubuntu18 Default=YES MaxTime=INFINITE State=UP OverSubscribe=NO
      PartitionName=batch Nodes=compute1 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO
      PartitionName=prod Nodes=compute1,ubuntu18 Default=NO MaxTime=INFINITE State=UP OverSubscribe=NO






      18.04





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      Check out our Code of Conduct.








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      asked 6 mins ago









      David CarterDavid Carter

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      David Carter is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






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