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[078-082] | 5 | 28 | 174000 | Intel(R) Xeon(R) Gold 6132 CPU @ 2.60GHz | v100 | 16GB GPU RAM per GPU | dlg2 |
| 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 |
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:
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: