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Private partition specifications

Deeplearn

The deeplearn partition has been bought for use by Computing and Information Systems research staff and students

Node name Nodes Cores/node Memory/node (MB) Processor GPU Type GPU Memory Slurm node type
spartan-gpgpu[086-088] 3 24 175000 Intel(R) Xeon(R) Silver 4214 CPU @ 2.20GHz v100sxm2 32GB GPU RAM per GPU dlg3
spartan-gpgpu[091-096] 6 32 234000 Intel(R) Xeon(R) Gold 6326 CPU @ 2.90GHz A100 40GB GPU RAM per GPU dlg4
spartan-gpgpu[065-071,132-143,160,166-169] 24 32 1000000 Intel(R) Xeon(R) Gold 6326 CPU @ 2.90GHz A100 80GB GPU RAM per GPU dlg5
spartan-gpgpu170 1 64 975000 Intel(R) Xeon(R) Platinum 8462Y+ H100 80GB GPU RAM per GPU dlg6

Note

The deeplearn partition is available to specific Computing and Information Systems projects only. You can request access to it at the time of creating a Spartan account, or by submitting a help ticket.

To access the deeplearn partition:

#SBATCH --partition=deeplearn
#SBATCH --qos=gpgpudeeplearn

To specify that your job should only run on a specific node type, add a constraint to your submission script. e.g. to specify the V100SXM2 nodes, add #SBATCH --constraint=dlg3 to your submit script.

feit-gpu-a100

The feit-gpu-a100 partition has been bought for use by FEIT research staff and students.

Node name Nodes Cores/node Memory/node (MB) Processor GPU Type GPU Memory Slurm node type
spartan-gpgpu[144-159,161-165] 21 32 1000000 Intel(R) Xeon(R) Gold 6326 CPU @ 2.90GHz A100 80GB GPU RAM per GPU

Note

The feit-gpu-a100 partition is available to FEIT projects only. You can request access to it at the time of creating a Spartan account, or by submitting a help ticket.

To access the feit-gpu-a100 partition:

#SBATCH --partition=feit-gpu-a100
#SBATCH --qos=feit