Partitions¶
In Slurm, partitions define job execution environments by grouping compute nodes with similar characteristics and applying scheduling policies to them.
Partitions typically specify:
- Hardware characteristics (e.g., CPU nodes, GPU nodes, memory size)
- Job limitations (e.g., maximum runtime, number of nodes)
- Scheduling parameters (e.g., priority tiers or quality of service)
Each job must be assigned to a partition either explicitly by the user or implicitly through a default partition configured by the cluster administrators.
The exact partitions available depend on the cluster configuration. Refer to the Devana partitions and Perun partitions for the list of available partitions and their limits.
To select a partition with a Slurm command, use the -p option:
srun | sbatch | salloc -p <partition> [...]
Example:
sbatch -p gpu myjob.sh
This submits the job to the partition named gpu.
Viewing Partitions and Their Definitions¶
Existing partions, included nodes, and general system state can be determined by the sinfo command.
Existing partitions and their current state can be displayed using the
sinfo command.
sinfo output
sinfo
PARTITION AVAIL TIMELIMIT NODES STATE NODELIST
cpu up 1-00:00:00 10 idle n[001-010]
gpu up 2-00:00:00 4 mix n[011-014]
testing up 30:00 2 idle login[01-02]
The columns show:
- PARTITION – partition name
- AVAIL – whether the partition is available
- TIMELIMIT – maximum allowed runtime
- NODES – number of nodes currently in this state
- STATE – node state (
idle,alloc,mix, etc.) - NODELIST – nodes belonging to the partition
The * next to a partition name indicates the default partition.
Partitions may appear on multiple lines because nodes can be in different states simultaneously.
Detailed Partition Information¶
More detailed partition configuration can be displayed with:
scontrol show partition
or for a specific partition:
scontrol show partition <partition>
Displaying information for a partition
scontrol show partition gpu
This command shows configuration parameters such as:
- maximum runtime
- node limits
- allowed accounts
- memory limits
- scheduling priority factors
Choosing the Right Partition¶
Selecting the appropriate partition is important for efficient scheduling. Jobs submitted to partitions with shorter time limits or more available resources are often scheduled faster.
If your job requirements exceed the limits of the available partitions, contact the HPC support team via the helpdesk.