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240x

prod-[001-240]

smp, smpht
mpp, mppht

• 2x AMD Rome Epyc 7702 (64 cores each) → 128 cores

• 256 GB RAM

• internal storage: /tmp: 314 GB NVMe

For our test phase, we have split the compute nodes in two sets, as announced by Malte in the HPC meeting:
-  smp,mpp: hyperthreading disabled (one thread per core)
-  smpht, mppht: hyperthreading enabled (2 threads per core).

More information can be found on the slurm documentation.

4x

fat-00[1-4]

fat, fatht

• like prod, but with

• 4 TB RAM

• internal storage:/tmp: 6.5 TB NVMe

1x

gpu-001

gpu

• like prod, but with
• 1 TB RAM

• internal storage:

  • /tmp: 3 TB NVMe

  • /scratch: 6.3 TB

• 2x Nvidia A40 GPU (48GB)

A comparison of the two different GPUs can be found here:
https://askgeek.io/en/gpus/vs/NVIDIA_A40-vs-NVIDIA_A100-SXM4-80-GB
The saying is: 

• How big are your models? Very, very big ⟹ A100

• Do you mainly work with mixed precision training (TensorFloat-32)? ⟹ A100

• Is FP32 more important? ⟹ A40

• Is FP64 more important? ⟹ A100

1x

gpu-002

gpu

• like prod, but with
• 1TB RAM

• internal storage:

  • /tmp: 3 TB NVMe
  • /scratch: 6.3 TB

• 4x Nvidia A100 GPU (80GB)