updated gpu profile to support process labels

conf/daisybio.config

@@ -84,11 +84,11 @@ profiles {
         docker.runOptions       = '-u $(id -u):$(id -g) --gpus all'
         apptainer.runOptions    = '--nv'
         singularity.runOptions  = '--nv'
-        process.queue = 'shared-gpu'
-        process.clusterOptions = '--qos=limitgpus --gpus=a40:1 --exclude compms-gpu-1.exbio.wzw.tum.de'
-        executor.queueSize = 5
+        process{
+            withLabel:process_gpu {
+                queue = 'shared-gpu'
+                clusterOptions = '--qos=limitgpus --gpus=a40:1 --exclude compms-gpu-1.exbio.wzw.tum.de'
+            }
+        }
     }
 }
-
-
-

docs/daisybio.md

@@ -7,6 +7,20 @@ This will automatically download and apply ['daisybio.config'](../conf/daisybio.
 The config file will set slurm as a scheduler for the compute cluster, define max resources, and specify cache locations for singularity, apptainer, and iGenomes.
 Pipeline-specific parameters still need to be configured manually.
 
-Work directories will be kept at `/nfs/scratch/nf-core_work/` in a directory named after the full path of the launch directory ("." separated). Thy are automatically removed after a successful pipeline run. To keep the intermediate file, e.g. for using the `-resume` function, add `keep_work` as a profile: `-profile daisybio,<singularity/apptainer>,keep_work`.
+## Keep work directories
 
-If you need GPU access, add `gpu` to the profile list to submit to the gpu queue: `-profile daisybio,<singularity/apptainer>,gpu`.
+Work directories will be kept at `/nfs/scratch/nf-core_work/` in a directory named after the full path of the launch directory ("." separated). They are automatically removed after a successful pipeline run. To keep the intermediate files, e.g. for using the `-resume` function, add `keep_work` as a profile: `-profile daisybio,<singularity/apptainer>,keep_work`.
+
+## GPU support
+
+If you need GPU access, add `gpu` to the profile list: `-profile daisybio,<singularity/apptainer>,gpu`.
+This will submit all processes labeled with `process_gpu` to our GPU queue.
+If you are using an nf-core pipeline, processes with GPU support should be already labeled correctly.
+If you are using a custom pipeline, you need to add the label to the process definition:
+
+```
+process YOURGPUPROCESS {
+    label 'process_gpu'
+    # ...
+}
+```