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edison
: 9 GPU nodes, 2-day runtime limitedison_k40m
: 5 GPU (k40m) nodes, 2-day runtime limitedison_k80
: 4 4 GPU (k80) nodes, 2-day runtime limit
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SCU cluster partitions:
- scu-cpu: 28 22 cpu nodes, 7-day runtime limit
- scu-gpu: 5 6 gpu nodes, 2-day runtime limit
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- cryo-cpu: 14 CPU-only nodes, 7-day runtime limit
- cryo-gpu: 6 GPU nodes, 2-day runtime limit
- cryo-gpu-v100: 3 2 GPU, 2-day runtime limit
- cryo-gpu-p100: 3 GPU, 2-day runtime limit
PI-specific cluster partitions:
- accardi_gpu: 4 GPU nodes, 2-day runtime lim
- accardi_cpu: 1 CPU node, 7-day runtime limit
boudker_gpu: 2 GPU nodes, 7-day runtime limit
- boudker_gpu-p100: 3 GPU nodes, 7-day runtime limit
- boudker_cpu: 2 CPU nodes, 7-day runtime limit
- sackler_ cpu: 1 CPU node, 7-day runtime limit
- sackler_ gpu: 1 GPU node, 7-day runtime limit
- hwlab-rocky_gpu: 12 GPU nodes, 7-day runtime limit
- sackler_ eliezer-gpu: 2 1 GPU node, 7-day runtime limit
Other specific cluster partitions:
- covid19scu-res: 1 CPUGPU, 7-day runtime limit
Of course, the above will be updated as needed; regardless, to see an up-to-date description of all available partitions, using the command sinfo
scu-login02. For a description of all the nodes' # CPU cores, memory (in Mb), runtime limits, and partition, use this command:
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srun -n1 --pty --partition=scu-cpu --mem=8G bash -i |
To request specific numbers of GPUs, you should add your request to your srun/sbatch:
Below is an example of requesting 1 GPU - can request up to 4 GPUs on a single node
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--gres=gpu:1 |
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A simple job submission example
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