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Table of Contents
outlinetrue

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  • edison: 9 GPU nodes, 2-day runtime limit
  • edison_k40m: 5 GPU (k40m) nodes, 2-day runtime limit
  • edison_k80: 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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Code Block
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

Code Block
--gres=gpu:1


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A simple job submission example

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