Partitions in Slurm can be considered as a resource abstraction. A partition configuration used to define resource limits and access controls for a group of nodes. Slurm allocates resources to jobs within the selected partition by taking into consideration the resources you request for your job and the partition's available resources and restrictions.
MFCF will adjust partition configurations as we observe usage patterns.
There are three partitions in the teaching GPU cluster: gpu-gen, gpu-k80, and gpu-gtx1080ti
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Use the gpu-gen partition when you don't care which type of GPU you use.
- gpu-gen total available resources:
Partition name gpu-gen Total available memory 600 GB Max Cores 78 cores Threads per core 2 Threads GPU devices 8 K80 devices, and
16 GTX1080ti devicesGPU memory per device 12 GB Compute Nodes gpu-pt1-02,
gpu-pt1-02,
gpu-pt1-03,
gpu-pt1-04gpu-gen partition specifications
- gpu-gen resource limits:
Max runtime (h) 12 hour Max Nodes 1 Node gpu-gen partition limits
- gpu-gen total available resources:
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Use the gpu-gtx1080ti partition to use the GTX1080i GPUs
- gpu-gtx1080ti total available resources:
Partition name gpu-gtx1080ti Total available memory 480 GB Max Cores 48 cores Threads per core 2 Threads GPU devices 8 GTX1080ti GPU memory per device 12 GB Compute Nodes gpu-pt1-02,
gpu-pt1-03gpu-gtx1080ti partition specifications - gpu-gtx1080ti resource limits:
Max runtime (h) 24 hours Max Nodes 1 Node gpu-gtx1080ti partition limits
- gpu-gtx1080ti total available resources: