UConn HPC profile Configuration
nf-core pipelines have been successfully configured for use on the UConn HPC cluster at Xanadu.
To use the xanadu profile, run the pipeline with -profile xanadu. This will download and apply xanadu.config which has been pre-configured for the UConn HPC cluster “Xanadu”. Using this profile, all Nextflow processes will be run within singularity containers, which can download and convert from docker containers when necesary.
A Nextflow module is available on the Xanadu HPC cluster, to use run module load nextflow or module load nextflow/<version> prior to running your pipeline. If you are expecting the NextFlow pipeline to consume more space than is available, you can set the work directory to /scratch/<userid> which can handle 84.TB with export NXF_WORK=/scratch/<userid>. CAUTION make sure to remove items from this directoy, it is not intended for long-term storage.
Config file
params {
config_profile_description = 'The UConn HPC profile'
config_profile_contact = 'noah.reid@uconn.edu'
config_profile_url = 'https://bioinformatics.uconn.edu/'
// max resources
max_memory = 2.TB
max_cpus = 64
max_time = 21.d
// Path to shared singularity images
singularity_cache_dir = '/isg/shared/databases/nfx_singularity_cache'
}
process {
resourceLimits = [
memory: 2.TB,
cpus: 64,
time: 21.d
]
executor = 'slurm'
queue = { task.memory <= 245.GB ? 'general' : (task.memory <= 512.GB ? 'himem' : 'himem2') }
clusterOptions = {
[
task.memory <= 245.GB ? '--qos=general' : '--qos=himem'
].join(' ').trim()
}
}
executor {
name = 'slurm'
submitRateLimit = '2 sec'
queueSize = 100
}
singularity {
enabled = true
cacheDir = params.singularity_cache_dir
autoMounts = true
conda.enabled = false
}
executor
contact
