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habrok:advanced_job_management:running_jobs_on_gpus [2023/09/11 13:01] – [Interactive GPU node] Created the section aurelhabrok:advanced_job_management:running_jobs_on_gpus [2024/11/22 08:10] (current) – [Available GPU types] fokke
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 </code> </code>
  
-where ''type'' is the type of GPU. Note that is is also still possible to use the ''%%--gres%%'' option that was required on Peregrine.+where ''type'' is the type of GPU. Note that it is also still possible to use the ''%%--gres%%'' option that was required on Peregrine.
  
 Jobs requesting GPU resources will automatically end up in one of the GPU partitions. Jobs requesting GPU resources will automatically end up in one of the GPU partitions.
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 ==== Available GPU types ==== ==== Available GPU types ====
  
-^ Node ^ GPU type ^  GPUs per node ^  Memory per GPU ^  CPUs per node ^  Memory per node ^ Slurm name ^ Notes ^ +^ Node ^ GPU type ^  GPUs per node ^  Memory per GPU ^  CPUs per node ^  Memory per node ^ Slurm name ^ 
-| A100_1 | Nvidia A100  |  4 |  40 GB |  64 |  512 GB | a100 | Full A100 cards | +| A100 | Nvidia A100  |  4 |  40 GB |  64 |  512 GB | a100 | 
-| A100_2 | Nvidia A100  |  8 |  20 GB |  64 |  512 GB | a100.20gb | Two virtual GPUs per A100 card | +| V100 | Nvidia V100  |  1 or 2 |  32 GB |  36 |  128 GB | v100 |
-| V100 | Nvidia V100  |  1 |  32 GB |  8|  128 GB | v100 | |+
  
 ==== Example ==== ==== Example ====
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 <code> <code>
 #SBATCH --gpus-per-node=a100:2 #SBATCH --gpus-per-node=a100:2
-</code> 
-If you want to request a node with half of an NVIDIA A100, use the following: 
- 
-<code> 
-#SBATCH --gpus-per-node=a100.20gb:1 
 </code> </code>
  
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 <code> <code>
-gpu1.hpc.rug.nl +gpu1.hb.hpc.rug.nl 
-gpu2.hpc.rug.nl+gpu2.hb.hpc.rug.nl
 </code> </code>
  
-These machines have an NVIDIA V100 GPU each, which can be shared by multiple users. The tool ''nvidia-smi'' will show if the GPU is in use. +These machines have an NVIDIA L40S GPU each, which can be shared by multiple users. The tool ''nvidia-smi'' will show if the GPU is in use. 
  
 ** Please keep in mind that this is a shared machine, so allow everyone to make use of these GPUs and do not perform long runs here. Long runs should be submitted as jobs to scheduler. ** ** Please keep in mind that this is a shared machine, so allow everyone to make use of these GPUs and do not perform long runs here. Long runs should be submitted as jobs to scheduler. **
 ==== Running interactive jobs ==== ==== Running interactive jobs ====
  
-You can request an interactive session by using a command like:+You can usually request an interactive session by using a command like:
 <code> <code>
 srun --gpus-per-node=1 --time=01:00:00 --pty /bin/bash srun --gpus-per-node=1 --time=01:00:00 --pty /bin/bash
 </code> </code>
 +
 +There is currently an issue with using ''srun --gpus-per-node'', but there is a workaround by using '' --gres'' instead:
 +<code>
 +srun --gres=gpu:1 --time=01:00:00 --pty /bin/bash
 +</code>
 +
 +or:
 +<code>
 +srun --gres=gpu:v100:1 --time=01:00:00 --pty /bin/bash
 +</code>
 +
  
 When the job starts running, you will be automatically logged in to the allocated node, allowing you to run your commands interactively. When you are done, just type ''%%exit%%'' to close your interactive job and to release the allocated resources. When the job starts running, you will be automatically logged in to the allocated node, allowing you to run your commands interactively. When you are done, just type ''%%exit%%'' to close your interactive job and to release the allocated resources.
  
 **N.B.: interactive jobs currently don't (always) use the software stack built for the allocated nodes, you can work around this by first running ''unset SW_STACK_ARCH && module restore'' after the job has started.** **N.B.: interactive jobs currently don't (always) use the software stack built for the allocated nodes, you can work around this by first running ''unset SW_STACK_ARCH && module restore'' after the job has started.**