FSL on ARC: Difference between revisions
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<code>someCommand</code> should probably be executing a shell script that includes | <code>someCommand</code> should probably be executing a shell script that includes | ||
export PATH=$FSLDIR/bin:$PATH | export PATH=$FSLDIR/bin:$PATH | ||
or | |||
export PATH=/build/fsl/bin:$PATH | |||
and your usual <code>eddy</code> script. | and your usual <code>eddy</code> script. | ||
In this container, <code>eddy_cuda</code> is called <code>eddy_cuda11.2</code> for the '''cuda toolkit''' version it works with. | In this container, <code>eddy_cuda</code> is called <code>eddy_cuda11.2</code> for the '''cuda toolkit''' version it works with. | ||
The <code>--nv</code> option says to look for a '''GPU''' so it will only work on a node with a gpu. | The <code>--nv</code> option says to look for a '''GPU''' so it will only work on a node with a gpu. | ||
Revision as of 21:46, 11 March 2024
Background
- Official Site: https://fsl.fmrib.ox.ac.uk
- Downloads and Registration:
FSL is a comprehensive library of analysis tools for FMRI, MRI and diffusion brain imaging data. It runs on macOS (Intel and M1/M2), Linux, and Windows via the Windows Subsystem for Linux, and is very easy to install. Most of the tools can be run both from the command line and as GUIs. To quote the relevant references for FSL tools you should look in the individual tools' manual pages, and also please reference one or more of the FSL overview papers.
Licensing
FSL is a licensed software and it is the property of Oxford University Innovation:
FSL container
The container is available to be copied to your home directory
/global/software/fsl/fsl-6.0.5/fsl605.sif
or it could be used directly from this location.
This is an apptainer (former singularity) container and can be run with the following line in your slurm script:
apptainer exec -B /work,/scratch,/bulk --nv /global/software/fsl/fsl-6.0.5/fsl605.sif someCommand
someCommand should probably be executing a shell script that includes
export PATH=$FSLDIR/bin:$PATH
or
export PATH=/build/fsl/bin:$PATH
and your usual eddy script.
In this container, eddy_cuda is called eddy_cuda11.2 for the cuda toolkit version it works with.
The --nv option says to look for a GPU so it will only work on a node with a gpu.
Requesting a GPU requires the lines
#SBATCH --partition=gpu-v100
#SBATCH --gres=gpu:1
Or similar ones for a100s