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# Slurm

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Slurm (also referred as Slurm Workload Manager or slurm-llnl) is an open-source workload manager designed for Linux clusters of all sizes, used by many of the world's supercomputers and computer clusters. It provides three key functions. First it allocates exclusive and/or non-exclusive access to resources (computer nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (typically a parallel job) on a set of allocated nodes. Finally, it arbitrates contention for resources by managing a queue of pending work.

## Installation

Install the slurm-llnl package. It pulls in munge ([1]), an authentication service, as a dependency. It is started as a requirement through slurmd's systemd service and encrypts the connection between the various hosts. Therefore make sure that all nodes in your cluster have the same key in `/etc/munge/munge.key`. Then start and enable `munge.service`.

The package itself has many more optional dependencies, though Slurm has to be recompiled to make use of them, after they have been installed.

## Configuration

The configuration files for slurm-llnl reside under `/etc/slurm-llnl`. Prior to starting any slurm-services, it has to be configured properly by creating a configuration file at `/etc/slurm-llnl/slurm.conf`. Client and server may use the same configuration file, which can either be generated at the official website or by copying `/etc/slurm-llnl/slurm.conf.example` to `/etc/slurm-llnl/slurm.conf` and adapting it to ones liking.

By default the Slurm user, which was introduced to your system in the installation process, has `64030` as UID and GID, this simplifies the setup on multiple systems. UID and GID matches the one used in Debian, therefore they may be used side-by-side, but remember that binaries are not in the same directories on each and every distribution.

### Client (compute node) configuration

On the client-side one may now safely start/enable `slurmd.service`.

Note If you choose to use Linux cgroups for process tracking, the `cgroup.conf` configuration file must be created on each client. See the cgroup.conf manual page for configuration details.

### Server (head node) configuration

Start/enable `slurmctld.service`.

Additionally you may want to start/enable `slurmdbd.service`, which handles a SQL database for easier management thereby logging somewhat essential process information.

Note Additional arguments may be passed to the program by adapting `/etc/default/slurm-llnl` though still utilizing the power of systemd. This file is handled as the environment file for the various services and simply passes any arguments on to the program.

## Troubleshooting

### Services fail to start on boot

If `slurmd.service` or `slurmctld.service` fail to start at boot but work fine when manually started, then the service may be trying to start before a network connection has been established. To verify this, add the lines associated with the failing service from below to the `slurm.conf` file:

    slurm.conf

    SlurmctldDebug=info
    SlurmctldLogFile=/var/log/slurm-llnl/slurmctld.log
    SlurmdDebug=info
    SlurmdLogFile=/var/log/slurm-llnl/slurmd.log

Then, check the associated log file. If you notice the fatal exception mentions `Address family not supported by protocol`, then you may want to extend the unit so that it waits for a valid network connection via network-online.target.

### Running RHEL based nodes side-by-side

On RedHat based distributions, slurm is running as root by default. [2] To add these nodes to the cluster, first create `slurm` user with `UID` and `GID` equal `64030` to match the one used in Arch Linux, then change slurm user with command `slurm-setuser -u slurm -g slurm`.

## See also

- Slurm tutorials — Introduction to the Slurm Workload Manager for users and system administrators, plus some material for Slurm programmers
- Quick Start Administrator Guide — Getting started guide
- Slurm to manage jobs — Convenient Slurm Commands
- Running Jobs — How Slurm is used at Harvard university

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- Distributed computing

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