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Slurm on Google Cloud Platform

The following describes setting up a Slurm cluster using Google Cloud Platform, bursting out from an on-premise cluster to nodes in Google Cloud Platform and setting a multi-cluster/federated setup with a cluster that resides in Google Cloud Platform.

Also, checkout the Slurm on GCP code lab.

The supplied scripts can be modified to work with your environment.

SchedMD provides professional services to help you get up and running in the cloud environment. SchedMD Commercial Support

Issues and/or enhancement requests can be submitted to SchedMD's Bugzilla.

For general feedback, please fill out the following form.

Stand-alone Cluster in Google Cloud Platform

The supplied scripts can be used to create a stand-alone cluster in Google Cloud Platform. The scripts setup the following scenario:

  • 1 - controller node
  • N - login nodes
  • N - compute nodes with a configured number of nodes that can be dynamically created to match workload.

The default image for the instances is CentOS 7.

On the controller node, slurm is installed in: /apps/slurm/<slurm_version> with the symlink /apps/slurm/current pointing to /apps/slurm/<slurm_version>.

The login nodes mount /apps and /home from the controller node.

To deploy, you must have a GCP account and either have the GCP Cloud SDK installed on your computer or use the GCP Cloud Shell.

Steps:

  1. Edit the slurm-cluster.yaml file and specify the required values

    For example:

    imports:
    - path: slurm.jinja
    
    resources:
    - name: slurm-cluster
      type: slurm.jinja
      properties:
        cluster_name            : g1
        static_node_count       : 2
        max_node_count          : 10
    
        zone                    : us-central1-b
        region                  : us-central1
        cidr                    : 10.10.0.0/16
    
        # Optional network configuration fields
        # READ slurm.jinja.schema for prerequisites
        #vpc_net                 : < my-vpc >
        #vpc_subnet              : < my-subnet >
        #shared_vpc_host_proj    : < my-shared-vpc-project-name >
    
        controller_machine_type : n1-standard-2
        compute_machine_type    : n1-standard-2
        login_machine_type      : n1-standard-2
        #login_node_count        : 0
    
        # Optional compute configuration fields
        #cpu_platform               : Intel Skylake
        #preemptible_bursting       : False
        #external_compute_ips       : False
        #private_google_access      : True
    
        #controller_disk_type       : pd-standard
        #controller_disk_size_gb    : 50
        #controller_labels          :
        #     key1 : value1
        #     key2 : value2
    
        #login_disk_type            : pd-standard
        #login_disk_size_gb         : 10
        #login_labels               :
        #     key1 : value1
        #     key2 : value2
    
        #compute_disk_type          : pd-standard
        #compute_disk_size_gb       : 10
        #compute_labels             :
        #     key1 : value1
        #     key2 : value2
    
        #nfs_apps_server            :
        #nfs_home_server            :
        #controller_secondary_disk          : True
        #controller_secondary_disk_type     : pd-standard
        #controller_secondary_disk_size_gb  : 300
    
        # Optional GPU configuration fields
        #gpu_type                   : nvidia-tesla-v100
        #gpu_count                  : 8
    
        # Optional timer fields
        #suspend_time               : 300
    
        #slurm_version           : 18.08-latest
        default_users           : < GCP user email addr, comma separated >
    
    

    NOTE: For a complete list of available options and their definitions, check out the schema file.

  2. Spin up the cluster.

    Assuming that you have gcloud configured for your account, you can just run:

    $ gcloud deployment-manager deployments [--project=<project id>] create slurm --config slurm-cluster.yaml
    
  3. Check the cluster status.

    You can see that status of the deployment by viewing: https://console.cloud.google.com/deployments

    and viewing the new instances: https://console.cloud.google.com/compute/instances

    To verify the deployment, ssh to the login node and run sinfo to see how many nodes have registered and are in an idle state.

    A message will be broadcast to the terminal when the installation is complete. If you log in before the installation is complete, you will either need to re-log in after the installation is complete or start a new shell (e.g. /bin/bash) to get the correct bash profile.

    $ gcloud compute [--project=<project id>] ssh [--zone=<zone>] g1-login1
    ...
    [bob@g1-login1 ~]$ sinfo
    PARTITION AVAIL  TIMELIMIT  NODES  STATE NODELIST
    debug*       up   infinite      8  idle~ g1-compute[3-10]
    debug*       up   infinite      2   idle g1-compute[1-2]
    

    NOTE: By default, Slurm will hide nodes that are in a power_save state -- "cloud" nodes. The GCP Slurm scripts configure PrivateData=cloud in the slurm.conf so that the "cloud" nodes are always shown. This is done so that nodes that get marked down can be easily seen.

  4. Submit jobs on the cluster.

    [bob@g1-login1 ~]$ sbatch -N2 --wrap="srun hostname"
    Submitted batch job 2
    [bob@g1-login1 ~]$ cat slurm-2.out
    g1-compute1
    g1-compute2
    
  5. Tearing down the deployment.

    $ gcloud deployment-manager [--project=<project id>] deployments delete slurm
    

    NOTE: If additional resources (instances, networks) are created other than the ones created from the default deployment then they will need to be destroyed before deployment can be removed.

Image-based Scaling

When a deployment is created, the deployment will create a <cluster_name>-compute-image instance that is a temporary compute instance image. When the instance is done installing packages, it then creates a image of itself and then destroys itself. Subsequent bursted compute instances will use this image -- shortening the creation and boot time of new compute instances. While the compute-image is running, the debug partition will be marked as "down" to prevent jobs from launching until the image is created. After the image is created, the partition will be put into an "up" state and jobs can then run.

NOTE: When creating a compute image that has gpus attached, the process can take about 10 minutes.

If the compute image needs to be updated, it can be done with the following command:

$ gcloud compute images create <cluster_name>-compute-image-<random> \
                               --source-disk <instance name> \
                               --source-disk-zone <zone> --force \
                               --family <cluster_name>-compute-image-family

Existing images can be viewed on the console's Images page.

Installing Custom Packages

There are two files: custom-controller-install, custom-compute-install in the scripts directory that can be used to add custom installations for the given instance type. The files will be executed during startup of the instance types.

Accessing Compute Nodes

There are multiple ways to connect to the compute nodes:

  1. If the compute nodes have external IPs you can connect directly to the compute nodes. From the VM Instances page, the SSH drop down next to the compute instances gives several options for connecting to the compute nodes.

  2. Whether the compute nodes have external IPs or not, they can be connected to from within the cluster. By default, the instances are setup with GCP's OSLogin.For information on managing access to instances see the OSLogin documentation.

    In general, you can click the "SSH" button next to the instance with an external IP on the VM Instances page. From this node you can ssh to compute nodes.

Preemptible VMs

With preemptible_bursting on, when a node is found preempted, or stopped, the slurm-gcp sync script will mark the node as "down" and will attempt to restart the node. If there were any batch jobs on the preempted node, they will be requeued -- interactive (e.g. srun, salloc) jobs can't be requeued.

Bursting out from on-premise cluster

Bursting out from an on-premise cluster is done by configuring the ResumeProgram and the SuspendProgram in the slurm.conf. The scripts resume.py, suspend.py and startup-script.py in the scripts directory can be modified and used create new compute instances in a GCP project. See the Slurm Elastic Computing for more information.

Bursting out playground

You can use the deployment scripts to create a playground to test bursting from an on-premise cluster by using two separate projects in GCP. This requires setting up a gateway-to-gateway VPN in GCP between the two projects. The following are the steps to do this.

  1. Create two projects in GCP (e.g. project1, project2).

  2. Create a slurm cluster in project1 using the deployments scripts.

    e.g.

    $ cat slurm-cluster.yaml
    resources:
    - name: slurm-cluster
      type: slurm.jinja
      properties:
        ...
        cluster_name            : g1
        ...
        cidr                    : 10.10.0.0/16
        ....
    
    $ gcloud deployment-manager --project=<project1> deployments create slurm --config slurm-cluster.yaml
    
  3. Create a network in project2.

    1. From the GCP console, navigate to VPC Network->VPC Networks->CREATE VPC NETWORK
    2. Fill in the following fields:
      Name                  : slurm-network2
      Subnets:
      Subnet creation mode  : custom
      Name                  : slurm-subnetwork2
      Region                : choose a region
      IP address range      : 10.20.0.0/16
      Private Google Access : Disabled
      Dynamic routing mode  : Regional
      
  4. Setup a gateway-to-gateway VPN.

    For each project, from the GCP console, create a VPN by going to Hybrid Connectivity->VPN->Create VPN connection.

    Fill in the following fields:

    Gateway:
    Name       : slurm-vpn
    Network    : choose project's network
    Region     : choose same region as slurm-network2's
    IP Address : choose or create a static IP
    
    Tunnels:
    Name                     : slurm-vpn-tunnel
    Remote peer IP Address   : static IP of other project
    IKE version              : IKEv2
    Shared secret            : string used by both vpns
    Routing options          : Policy-based
    Remote network IP ranges : IP range of network of other project (Enter 10.20.0.0/16 for project1 and 10.10.0.0/16 for project2)
    Local subnetworks        : For project1 choose "slurm-network" and for project2 choose "slurm-network2"
    Local IP ranges          : Should be filled in with the subnetwork's IP range.
    

    Then click Create.

    If all goes well then the VPNs should show a green check mark for the VPN tunnels.

  5. Add permissions for project1 to create instances in project2.

    By default, GCE will create a service account in the instances that are created. We need to get this account name and give it permissions in project2.

    1. gcloud compute ssh to controller in project1
    • $ gcloud compute [--project=] ssh [--zone=] g1-controller
    1. Run:
      gcloud config list
      
    2. Grab the account name.
    3. From project2's GCP Console, navigate to: IAM & Admin.
    4. Click ADD at the top.
    5. Add the account name to the Members field.
    6. Select the Compute Admin and Service Account User roles.
    7. Click ADD
  6. Modify resume.py and suspend.py in the /apps/slurm/scripts directory on project1's controller instance to communicate with project2.

    Modify the following fields with the appropriate values: e.g.

    # resume.py, suspend.py
    PROJECT      = '<project2 id>'
    ZONE         = '<project2 zone>'
    
    # resume.py
    REGION       = '<project2 region>'
    
    # Set to True so that it can install packages from the other network
    EXTERNAL_IP  = True
    
  7. Configure the instances to be able to find the controller node.

    Modify startup-script.py to put the controller's IP address in /etc/hosts. You can find the controller's internal IP address by navigating to Compute Engine in project1's GCP Console.

    e.g.

    diff --git a/scripts/startup-script.py b/scripts/startup-script.py
    index 018c270..6103c5e 100644
    --- a/scripts/startup-script.py
    +++ b/scripts/startup-script.py
    @@ -704,6 +704,12 @@ PATH=$PATH:$S_PATH/bin:$S_PATH/sbin
    
     def mount_nfs_vols():
    
    +    f = open('/etc/hosts', 'a')
    +    f.write("""
    +<controller ip> controller
    +""")
    +    f.close()
    +
         f = open('/etc/fstab', 'a')
         f.write("""
     controller:{0}    {0}     nfs      rw,sync,hard,intr  0     0
    
  8. Since the scripts rely on getting the Slurm configuration and binaries from the shared /apps file system, the firewall on the project1 must be modified to allow NFS through.

    1. On project1's GCP Console, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : nfs
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : Specified target tags
      Target tags          : controller
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:2049,1110,4045; udp:2049,1110,4045
      
    4. Click Create
  9. Open ports on project1 for project2 to be able to contact the slurmctld (tcp:6820) and the slurmdbd (tcp:6819) on project1.

    1. On project1's GCP Console, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : slurm
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : Specified target tags
      Target tags          : controller
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:6820,6819
      
    4. Click Create
  10. Open ports on project2 for project1 to be able to contact the slurmd's (tcp:6818) in project2.

    1. On project2's GCP Console, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : slurmd
      Network              : project2-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : Specified target tags
      Target tags          : compute
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:6818
      
    4. Click Create
  11. If you plan to use srun to submit jobs from the login nodes to the compute nodes in project2, then ports need to be opened up for the compute nodes to be able to talk back to the login nodes. srun open's several ephemeral ports for communications. It's recommended to define which ports srun can use when using a firewall. This is done by defining SrunPortRange= in the slurm.conf.

    e.g.

    SrunPortRange=60001-63000
    

    These ports need to opened up in project1 and project2's firewalls.

    1. On project1 and project2's GCP Consoles, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : srun
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : All instances in the network
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:60001-63000
      
    4. Click Create
  12. Slurm should now be able to burst out into project2.

Multi-Cluster / Federation

Slurm allows you to use a central SlurmDBD for multiple clusters. By doing this it also allows the clusters to be able to communicate with each other. This is done by the client commands first checking with the SlurmDBD for the requested cluster's IP address and port which the client can then communicate directly with the cluster.

For more information see:
Multi-Cluster Operation
Federated Scheduling Guide

NOTE: Either all clusters and the SlurmDBD must share the same MUNGE key or use a separate MUNGE key for each cluster and another key for use between each cluster and the SlurmDBD. In order for cross-cluster interactive jobs to work, the clusters must share the same MUNGE key. See the following for more information:
Multi-Cluster Operation
Accounting and Resource Limits

NOTE: All clusters attached to a single SlurmDBD must share the same user space (e.g. same uids across all the clusters).

Playground

  1. Create another project in GCP (e.g. project3) and create another Slurm cluster using the deployment scripts -- except with a different cluster name (e.g. g2) and possible IP range.

  2. Open ports on project1 so that project3 can communicate with project1's slurmctld (tcp:6820) and slurmdbd (tcp:6819).

    1. On project1's GCP Console, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : slurm
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : Specified target tags
      Target tags          : controller
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:6820,6819
      
    4. Click Create
  3. In project3 open up ports for slurmctld (tcp:6820) so that project1 can communicate with project3's slurmctld.

    1. On project3's GCP Console, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : slurm
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : Specified target tags
      Target tags          : controller
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:6820
      
    4. Click Create
  4. Optional ports for interactive jobs.

    If you plan to use srun to submit jobs from one cluster to another, then ports need to be opened up for srun to be able to communicate with the slurmds on the remote cluster and ports need to be opened for the slurmds to be able to talk back to the login nodes on the remote cluster. srun open's several ephemeral ports for communications. It's recommended to define which ports srun can use when using a firewall. This is done by defining SrunPortRange= in the slurm.conf.

    e.g.

    SrunPortRange=60001-63000
    

    NOTE: In order for cross-cluster interactive jobs to work, the compute nodes must be accessible from the login nodes on each cluster (e.g. a vpn connection between project1 and project3).

    slurmd ports:

    1. On project1 and project3's GCP Console, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : slurmd
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : Specified target tags
      Target tags          : compute
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:6818
      
    4. Click Create

    srun ports:

    1. On project1 and project3's GCP Consoles, navigate to VPC network->Firewall rules
    2. Click CREATE FIREWALL RULE at the top of the page.
    3. Fill in the following fields:
      Name                 : srun
      Network              : slurm-network
      Priority             : 1000
      Direction of traffic : Ingress
      Action to match      : Allow
      Targets              : All instances in the network
      Source Filter        : IP ranges
      Source IP Ranges     : 0.0.0.0/0
      Second source filter : none
      Protocols and ports  : Specified protocols and ports
      tcp:60001-63000
      
    4. Click Create
  5. Modify both project1 and project3's slurm.confs to talk to the slurmdbd on project1's external IP.

    e.g.

    AccountingStorageHost=<external IP of project1's controller instance>
    
  6. Add the cluster to project1's database.

    e.g.

    $ sacctmgr add cluster g2
    
  7. Add user and account associations to the g2 cluster.

    In order for a user to run a job on a cluster, the user must have an association on the given cluster.

    e.g.

    $ sacctmgr add account <default account> [cluster=<cluster name>]
    $ sacctmgr add user <user> account=<default account> [cluster=<cluster name>]
    
  8. Restart the slurmctld on both controllers.

    e.g.

    $ systemctl restart slurmctld
    
  9. Verify that the slurmdbd shows both slurmctld's have registered with their external IP addresses.

    • When the slurmctld registers with the slurmdbd, the slurmdbd records the IP address the slurmctld registered with. This then allows project1 to communicate with project3 and vice versa.

    e.g.

    $ sacctmgr show clusters format=cluster,controlhost,controlport
       Cluster     ControlHost  ControlPort
    ---------- --------------- ------------
            g1 ###.###.###.###         6820
            g2 ###.###.###.###         6820
    
  10. Now you can communicate with each cluster from the other side.

    e.g.

    [bob@login1 ~]$ sinfo -Mg1,g2
    CLUSTER: g1
    PARTITION AVAIL  TIMELIMIT  NODES  STATE NODELIST
    debug*       up   infinite      8  idle~ g1-compute[3-10]
    debug*       up   infinite      2   idle g1-compute[1-2]
    
    CLUSTER: g2
    PARTITION AVAIL  TIMELIMIT  NODES  STATE NODELIST
    debug*       up   infinite      8  idle~ g2-compute[3-10]
    debug*       up   infinite      2   idle g2-compute[1-2]
    
    [bob@login1 ~]$ sbatch -Mg1 --wrap="srun hostname; sleep 300"
    Submitted batch job 17 on cluster g1
    
    [bob@login1 ~]$ sbatch -Mg2 --wrap="srun hostname; sleep 300"
    Submitted batch job 8 on cluster g2
    
    [bob@login1 ~]$ squeue -Mg1,g2
    CLUSTER: g1
                 JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
                    17     debug     wrap      bob  R       0:31      1 g1-compute1
    
    CLUSTER: g2
                 JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
                     8     debug     wrap      bob  R       0:12      1 g2-compute1
    

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