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slide to change on the other.
Useful when presenting.
job_config
in galaxy.yml
, group_vars/galaxyservers.yml
, and files/galaxy/config/tpv*.yml
Correspond to job runner plugins in lib/galaxy/jobs/runners
Plugins for:
pbs_python
libraryenv
key in environments: configure the job execution environment
syntax | function |
---|---|
- {name: NAME, value: VALUE} |
Set $NAME to VALUE |
- {file: /path/to/file} |
Source shell file at /path/to/file |
- {execute: CMD} |
Execute CMD |
Source and command execution will be handled on the remote destination, don't need to work on the Galaxy server
Our simple example works because of two important principles:
/srv/galaxy/server
)The first can be worked around with symlinks, copies, or Pulsar embedded
The second can be worked around with Pulsar REST/MQ (with a performance/throughput penalty)
Some tools can greatly improve performance by using multiple cores
Galaxy automatically sets $GALAXY_SLOTS
to the CPU/core count you specify when submitting, for example, 4:
sbatch --ntasks=4
qsub -pe threads 4
qsub -l nodes=1:ppn=4
request_cpus: 4
Tool configs: Consume \${GALAXY_SLOTS:-4}
For Slurm and Gridengine only, Galaxy will set $GALAXY_MEMORY_MB
and $GALAXY_MEMORY_MB_PER_SLOT
as integers.
Other DRMs: Please PR the appropriate code.
For Java tools, be sure to set -Xmx
, e.g.:
java_cluster: runner: drmaa env: - name: '_JAVA_OPTIONS' value: '-Xmx6G'
If your Galaxy users == System users:
A special built-in job runner plugin
Map jobs to destinations on more than just tool IDs
Two types:
See: Dynamic Destination Mapping
Powerful, fully dynamic tool-to-environment mapping based on tool, user, resource requirements, tags, and more.
Discussed in detail in its own tutorial.
See also: TPV Documentation.
Programmable mappings:
lib/galaxy/jobs/rules/
sbatch
params)This material is the result of a collaborative work. Thanks to the Galaxy Training Network and all the contributors!
Author(s) |
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Reviewers |
|
Tutorial Content is licensed under Creative Commons Attribution 4.0 International License.
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