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GPU Type

Partition

Example slurm value to request

# of Nodes

GPU devices per node

CUDA Cores

Tensor Cores

GPU Memory Size (GB)

Compute Capability

Tesla P100

teton-gpu

(all available on non-investor)

Code Block
#SBATCH --partition=teton-gpu #SBATCH --gres=gpu:?<#_gpu_requested>

8

2

3584

0

16

6.0

V100

dgx

(both available on non-investor)

Code Block
#SBATCH --partition=dgx #SBATCH --gres=gpu:?<#_gpu_requested>

2

8

5120

640

16/32

7.0

A30

beartooth-gpu (4)

mb-a30 (8)

non-investor (3)

Code Block
#SBATCH --partition=beartooth-gpu #SBATCH --gres=gpu:?<#_gpu_requested>

15

7 on BT/non-investor, 8 on MedicineBow

3584

224

25

8.0

T4

non-investor

Code Block
#SBATCH --partition=beartooth-gpu #SBATCH --gres=gpu:<#_gpu_requested>

2

3

2560 or
3804 FP32 CUDA/GPU on MB

320 or 224 TC/GPU on MB

16G
24GB/GPU on MB

7.5

L40S

mb-l40s (5)

Code Block
#SBATCH --partition=beartooth-gpu #SBATCH --gres=gpu:<#_gpu_requested>

5

8

568 TC/GPU on MB

48GB/GPU

H100

mb-h100 (6)

Code Block
#SBATCH --partition=beartooth-gpu #SBATCH --gres=gpu:<#_gpu_requested>

6

8

16896 FP32 CUDA/GPU

528 TC/GPU on MB

80GB/GPU

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