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The compute nodes of Lise in Berlin (blogin.hlrn.de) and Emmy in Göttingen (glogin.hlrn.de) are organized via the following SLURM partitions:

The following GPU partitions are available on Lise.

gpu-a100

4x A100 per Node

full node exclusive

# run command on two MPI nodes in the exclusive use partition
srun -N 2 -p gpu-a100 example_ cmd

gpu-a100:shared

1 to 4 A100

shared node access, exclusive use of the requested GPUs

# run command using GPUs (-G/--gpus) in the shared node partition
srun -G 2 -p gpu-a100:shared example_cmd

gpu-a100:shared:mig

1 to 28 1g.10gb A100 MIG slices

shared node access, shared GPU devices via Multi Instance GPU.
Each of the four GPUs is logically split into usable seven slices with 10 GB of GPU memory associated to each slice

# run command using one Multi Instance GPU slice on the according partition
srun -G 1 -p gpu-a100:shared:mig example_cmd

Lise (Berlin)

Partition (number holds cores per node)	Node name	Max. walltime	Nodes	Max. nodes per job	Max jobs (running/ queued) per user	Usable memory MB per node	CPU	Shared	Charged core-hours per node	Remark
standard96	bcn#	12:00:00	1204	512	16 / 500	362 000	Cascade 9242	✘	96	default partition

standard96:test	bcn#	1:00:00	32 dedicated +128 on demand	16	1 / 500	362 000	Cascade 9242	✘	96	test nodes with higher priority but lower walltime
large96	bfn#	12:00:00	28	8	16 / 500	747 000	Cascade 9242	✘	144	fat memory nodes
large96:test	bfn#	1:00:00	2 dedicated +2 on demand	2	1 / 500	747 000	Cascade 9242	✘	144	fat memory test nodes with higher priority but lower walltime
large96:shared	bfn#	48:00:00	2 dedicated	1	16 / 500	747 000	Cascade 9242	✓	144	fat memory nodes for data pre- and postprocessing
huge96	bsn#	24:00:00	2	1	16 / 500	1522 000	Cascade 9242	✓	192	very fat memory nodes for data pre- and postprocessing

...

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Alte Version 4

Neue Version 5

Schlüssel

Lise (Berlin)