nf-core/configs: mccleary
McCleary Cluster at Yale
nf-core/configs: McCleary Configuration
All nf-core pipelines have been successfully configured for use on the Yale University McCleary cluster. To use, run the pipeline with -profile mccleary.
NB: You will need an account to use the HPC cluster on the McCleary cluster in order to run the pipeline. If in doubt contact IT. To use nf-core pipelines on McCleary:
- Install Nextflow for your user. Move the Nextflow executable to a folder in your
$PATHvariable (e.g.~/bin).
module load Java/17.0.4
curl -s https://get.nextflow.io | bash
- Submit your pipeline script via
sbatch script.sh. With the following script. Update--job-name,—time, and—partition` as needed for your head job. 2 CPUs and 5GB of memory is usually sufficient for the Nextflow head job but you can also update as needed.
#! /bin/bash
#SBATCH --job-name=nf-core
#SBATCH --out="slurm-%j.out"
#SBATCH --time=07-00:00:00
#SBATCH --cpus-per-task=2
#SBATCH --mem=5G
#SBATCH --mail-type=ALL
#SBATCH --partition=week
module load Java/17.0.4
export NXF_WRAPPER_STAGE_FILE_THRESHOLD='40000'
nextflow pull nf-core/<pipeline> -r <release>
nextflow run nf-core/<pipeline> -r <release> \
-profile mccleary \
--outdir "results" \
...
Pipeline Specific profiles
There are no specific profiles added for now
Config file
//Profile config names for nf-core/configsparams { config_profile_name = 'mccleary' config_profile_description = 'McCleary Cluster at Yale' config_profile_contact = 'Gisela Gabernet, @ggabernet' config_profile_url = 'https://docs.ycrc.yale.edu/clusters/mccleary/'
}
singularity { enabled = true}
executor { name = 'slurm' queueSize = 50 submitRateLimit = '190/60min'}
process { resourceLimits = [ memory: 983.GB, cpus: 64 ] queue = { task.time > 24.h ? 'week' : task.attempt < 3 ? 'scavenge' : 'day' } errorStrategy = { task.exitStatus in (1) ? 'finish' : 'retry' } max_retries = 2 scratch = 'true' executor = 'slurm' withLabel:'process_gpu'{ queue = 'gpu' accelerator = 1 clusterOptions = "--gpus=1" containerOptions = { workflow.containerEngine == "singularity" ? '--nv': ( workflow.containerEngine == "docker" ? '--gpus all': null ) } memory = 32.GB time = 24.h }}