Allocating resources

When running jobs, you can request specific resources like memory, CPUs, and GPUs.

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💾 System memory

--mem=40G

⚙️ CPUs

--cpus-per-task=15

🎮 GPUs

--gres=gpu:1

GPU Resource Limits

To ensure fair access for all users, AI-LAB enforces two important limits:

• Maximum 4 GPUs per job: A single job can request no more than 4 GPUs (e.g., --gres=gpu:4)
• Maximum 8 GPUs per user: Each user can run jobs using a total of up to 8 GPUs simultaneously across all their running jobs

We strongly encourage inexperienced users to allocate only 1 GPU, as most workloads do not speed up automatically with more GPUs.

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🚀 Example: Allocating resources with srun

srun --cpus-per-task=4 --mem=8G --gres=gpu:1 python3 my_script.py

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📝 Example: Allocating resources with sbatch

In a batch script, add resource requests using #SBATCH directives:

run.sh

#!/bin/bash
#SBATCH --gres=gpu:1          # Request 1 GPU
#SBATCH --cpus-per-task=4    # Request 4 CPUs
#SBATCH --mem=8G             # Request 8 GB memory

python3 my_script.py

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