Page Comparison

...

• panda: 70 CPU-only nodes, 7-day runtime limit

Edison cluster:

• edison: 9 GPU nodes, 2-day runtime limit
• edison_k40m: 5 GPU (k40m) nodes, 2-day runtime limit
• edison_k80: 4 4  GPU (k80) nodes, 2-day runtime limit

...

SCU cluster partitions:

• scu-cpu: 21 22 cpu nodes, 7-day runtime limit
• scu-gpu: 6 gpu nodes, 2-day runtime limit

...

• 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
• eliezer-gpu: 12  1 GPU nodesnode, 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:

...

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

--gres=gpu:1

...

A simple job submission example

...