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

Lise (Berlin)

Partition (number holds cores per node)

Node nameMax. walltimeNodesMax. nodes
per job

Max jobs (running/ queued)
per user

Usable memory MB per node

CPU

Shared

Charged core-hours per node

Remark
standard96bcn#12:00:001204512

16 / 500

362 000Cascade 924296default partition
standard96:testbcn#1:00:0032 dedicated
+128 on demand
161 / 500362 000Cascade 924296test nodes with higher priority but lower walltime
large96bfn#12:00:0028816 / 500747 000Cascade 9242144fat memory nodes
large96:testbfn#1:00:002 dedicated
+2 on demand
21 / 500747 000Cascade 9242144fat memory test nodes with higher priority but lower walltime
large96:sharedbfn#48:00:002 dedicated116 / 500

747 000

Cascade 9242144fat memory nodes for data pre- and postprocessing
huge96bsn#24:00:002116 / 500

1522 000

Cascade 9242192

very fat memory nodes for data pre- and postprocessing

12 hours are too short? See here how to pass the 12h walltime limit with job dependencies.

Emmy (Göttingen)

Partition (number holds cores per node)

Node name

Max. walltime

NodesMax. nodes
per job
Max. jobs
per user

Usable memory MB per node

CPU, GPU type

SharedNPL per node hourRemark
standard96

gcn#

12:00:00924256unlimited362 000Cascade 924296default partition
standard96:testgcn#1:00:0016 dedicated
+48 on demand
16unlimited362 000Cascade 924296test nodes with higher priority but lower walltime
large96gfn#12:00:00122unlimited747 000Cascade 9242144fat memory nodes
large96:testgfn#1:00:002 dedicated
+2 on demand
2unlimited747 000Cascade 9242144fat memory test nodes with higher priority but lower walltime
large96:sharedgfn#48:00:002 dedicated +2 on demand1unlimited

747 000

Cascade 9242144fat memory nodes for data pre- and postprocessing
huge96gsn#24:00:0021unlimited

1522 000

Cascade 9242192

very fat memory nodes for data pre- and postprocessing












medium40gcn#48:00:00368128unlimited181 000Skylake  614840
medium40:testgcn#1:00:00

32 dedicated

+96 on demand

8unlimited

181 000

Skylake  614840test nodes with higher priority but lower walltime
large40gfn#48:00:00114unlimited

764 000

Skylake  614880fat memory nodes
large40:testgfn#1:00:0032unlimited

764 000

Skylake  614880fat memory test nodes with higher priority but lower walltime
large40:sharedgfn#48:00:0021unlimited764 000Skylake  614880fat memory nodes for data pre- and postprocessing
gpuggpu#12:00:0033unlimited

764MB per node

(32GB per gpu)

Skylake  6148 + 4 Tesla V100600



see GPU Usage



gpu40



unlimited(40GB per gpu)?????? + 4 NVidia A100
600

Which partition to choose?

If you do not request a partition, your job will be placed in the default partition, which is standard96.

The default partitions are suitable for most calculations. The :test partitions are, as the name suggests, intended for shorter and smaller test runs. These have a higher priority and a few dedicated nodes, but are limited in time and number of nodes. Shared nodes are suitable for pre- and postprocessing. A job running on a shared node is only accounted for its core fraction (cores of job / all cores per node). All non-shared nodes are exclusive to one job, which implies that full NPL are paid.

Details about the CPU/GPU types can be found below.
The network topology is described here.

The available home/local-ssd/work/perm storages are discussed in File Systems.

An overview of all partitions and node statuses is provided by: sinfo -r
To see detailed information about a nodes type: scontrol show node <nodename>

List of CPUs and GPUs at HLRN


Short nameLink to manufacturer specificationsWhere to findUnits per node

Cores per unit

Clock speed
[GHz]

Cascade 9242Intel Cascade Lake Platinum 9242 (CLX-AP)Lise and Emmy compute partitions2482.3
Cascade 4210Intel Cascade Lake Silver 4210 (CLX)blogin[1-8], glogin[3-8]2102.2
Skylake  6148Intel Skylake Gold 6148Emmy compute partitions2202.4
Skylake 4110Intel Skylake Silver 4110glogin[1-2]282.1
Tesla V100NVIDIA Tesla V100 32GBEmmy gpu partition4

640/5120*


*Tensor Cores / CUDA Cores