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Extension of the basic BRIG - like rings and annotations to some more specific applications:
Antimicrobial resistance predictions for automatic generation of labels with abritAMR
Probability of viral, plasmid or chromosomal origin along segments of the reference genome with geNomad
Add styling and provide arc line specific options, add geNomad prediction class selection
For long running tasks we want to:
Celery: adjust timeout for task result requests to 10min - if these timeout, the data is still processed and dumped into the database model, meaning while e.g. a ring is not added, on reload the updated session model is visualised
Celery: test different settings for file uploads and long running tasks
App: perhaps we need a job table which contains a log of submitted and completed/failed jobs maybe at a later stage, working relatively smoothly now
Server: keep a copy of the output tagged by reference sequence or similar to avoid redundant re-computing
Server: limit threads in case of high load on these tasks, both on Celery workers and as setting for subprocesses
Server: limit worker container memory for tasks, or implement proper workflow scheduler for intensive pipelines
Server Profile geNomad memory consumption to set limits on worker container
Adding the --splits argument to genomad execution to reduce memory footprint for now. See if timeout limits have to be adjusted. These arguments can all set through the FastAPI settings and when deploying the stack through the docker/brick.env stack configuration variables.
Intensive bioinformatics tasks are not meant to run in task schedulers, especially considering resource management. Need a better solution also for other projects, any suggestions welcome!
The text was updated successfully, but these errors were encountered:
Extension of the basic
BRIG
- like rings and annotations to some more specific applications:abritAMR
geNomad
geNomad
prediction class selectionFor long running tasks we want to:
maybe at a later stage, working relatively smoothly nowApp
: perhaps we need a job table which contains a log of submitted and completed/failed jobsServer
: keep a copy of the output tagged by reference sequence or similar to avoid redundant re-computingServer
: limit threads in case of high load on these tasks, both on Celery workers and as setting for subprocessesServer
: limit worker container memory for tasks, or implement proper workflow scheduler for intensive pipelinesServer
Profile geNomad memory consumption to set limits on worker containerAdding the
--splits
argument togenomad
execution to reduce memory footprint for now. See if timeout limits have to be adjusted. These arguments can all set through theFastAPI
settings and when deploying the stack through thedocker/brick.env
stack configuration variables.Intensive bioinformatics tasks are not meant to run in task schedulers, especially considering resource management. Need a better solution also for other projects, any suggestions welcome!
The text was updated successfully, but these errors were encountered: