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# nf-core/configs: LUGH configuration # nf-core/configs: LUGH configuration
To use the lugh configuration profile with your pipeline, add `-profile lugh` to your `nextflow run` command. Please take care to use the `-bg` flag or run the job on a compute node. DO NOT RUN ANALYSES ON THE HEAD NODE. Author: Barry Digby
Contact Info: barry.digby@nuigalway.ie
System Administrator: Chris Duke
The configuration file will load prerequisite modules for users, however it is entirely up to the user to have a functional version of nextflow installed in their path. ## Quick Start
Lugh has 3 queues: To use the lugh configuration profile with your pipeline, add `-profile lugh` to your `nextflow run` command:
* `MSC`: compute0{1..3}, 16 cpus, 32GB memory (Please reserve for MSc students only) ```console
* `normal`: compute{10..29}, 16 cpus, 64GB memory. nextflow -bg run nf-core/rnaseq -profile test,nuig
& `highmem`: compute0{4..9}, 32 cpus, 128GB memory. ```
The configuration profile design is very simple. If your process exceeds 64GB memory or 16 cpus, it is sent to the `highmem` queue. Else, `normal`. Please take care to use the `-bg` flag, or run the job on a compute node.
Whilst I (@BarryDigby) am happy to help people set up their nextflow pipelines, please note that I am not the system administrator. :warning: DO NOT RUN ANALYSES ON THE HEAD NODE :warning:
The configuration file will load prerequisite modules for users (`Java` & `Singularity`), however it is up to the user to have a functional version of `nextflow` installed in their path. Follow `nextflow` installation instructions at the following (link)[https://www.nextflow.io/docs/latest/getstarted.html#installation].
## Queue Resources
| Queue | Hostnames | Max Memory | Max CPUS | Max Time |
|--------- |---------------- |------------ |---------- |---------- |
| MSC | compute[01-03] | 32GB | 16 | 336.h |
| Normal | compute[10-29] | 64GB | 16 | 240.h |
| Highmem | compute[04-09] | 128GB | 32 | 2880.h |
***
The configuration profile design is very simple. If your process exceeds 64GB memory or 16 cpus, it is sent to the `highmem` queue. If not, it is sent to the `normal` queue. Please do not use the `MSC` queue, this is reserved for Masters students.
Take others into consideration when deploying your workflow (do not hog the cluster :pig:). If you need to hammer the cluster with a pipeline, please reach out to me and we can tweak the configuration profile to dispatch jobs to only a handful of compute nodes via hostnames.
## Container Cache ## Container Cache
Your workflow containers will be downloaded and stored at `/data/containers` which is accessible to all users. Your workflow containers are stored under `/data/containers/` which is accessible to all users on lugh.