This article will guide you to run the Python script using Slurm script on a describes how to execute a Python script on the LANTA HPC system . You can find using Miniconda. The following table of contents provides an overview of the content from the table of contents below for immediate viewing of the interesting article's material, allowing for quick identification of the most relevant sections.
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Slurm script example for running
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the Python script
Running on Compute node
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#!/bin/bash #SBATCH -p compute # Specify partition [Compute/Memory/GPU] #SBATCH -N 1 -c 128 # Specify number of nodes and processors per task #SBATCH --ntasks-per-node=1 # Specify tasks per node #SBATCH -t 120:00:00 # Specify maximum time limit (hour: minute: second) #SBATCH -A ltxxxxxx # Specify project name #SBATCH -J JOBNAME # Specify job name module purge # Unload all modules module load Miniconda3Mamba/2223.11.1-10-0 # Load the Miniconda3conda module conda activate tensorflow-2.612.01 # Activate your environment python3 file.py # Run your program or executable code |
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Full node: -c 128, Half node: -c 64, ΒΌ node: -c 32 |
Running on GPU node
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#!/bin/bash #SBATCH -p gpu # Specify partition [Compute/Memory/GPU] #SBATCH -N 1 -c 16 # Specify number of nodes and processors per task #SBATCH --gpus-per-task=1 # Specify number of GPU per task #SBATCH --ntasks-per-node=4 # Specify tasks per node #SBATCH -t 120:00:00 # Specify maximum time limit (hour: minute: second) #SBATCH -A ltxxxxxx # Specify project name #SBATCH -J JOBNAME # Specify job name module purge # Unload all modules module load Miniconda3Mamba/2223.11.1-10-0 # Load the Miniconda3conda module conda activate tensorflow-2.612.01 # Activate your environment python3 file.py # Run your program or executable code |
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1 GPU card: --ntasks-per-node=1, 2 GPU cards: --ntasks-per-node=2, 4 GPU cards: --ntasks-per-node=4 |
Submit a job
Use the sbatch script.sh commands command to submit your job to the Slurm system.
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username@lanta:~> sbatch script.sh |
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Before you use the |
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