File size: 6,014 Bytes
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default: ""
type: file
title: "Path to the CNS executable"
short: If not provided, HADDOCK3 will use the cns path configured
during the installation.
long: CNS is a required component to run HADDOCK. Ideally it should have been
configured during installation. If not you can specify with the cns_exec parameter
its path.
group: "execution"
explevel: easy
ncores:
default: 4
type: integer
min: 1
max: 500
title: Number of CPU cores
short: Number of CPU cores to use for the CNS calculations.
It is truncated to max available CPUs minus 1.
long: Number of CPU cores to use for the CNS calculations.
This will define the number of concurrent jobs being executed.
Note that is truncated to the total number of available CPUs minus 1.
group: "execution"
explevel: easy
max_cpus:
default: true
type: boolean
title: The max number of CPUs allowed.
short: By default the max number of CPUs allowed is the max available on the system.
long:
If you want to spare a minimum amount of resources for daily tasks, set max_cpus
to false; in that case the maximum number of CPUs allowed will be the total available
in the machine minus 1. This calculation is done automatically.
group: "execution"
explevel: expert
mode:
default: local
type: string
minchars: 0
maxchars: 20
choices:
- local
- batch
title: Mode of execution
short: Mode of execution of the jobs, either local or using a batch system.
long: Mode of execution of the jobs, either local or using a batch system.
Currently slurm and torque are supported. For the batch mode the queue command must be
specified in the queue parameter.
group: "execution"
explevel: easy
batch_type:
default: "slurm"
type: string
minchars: 0
maxchars: 100
choices:
- slurm
- torque
title: Batch system
short: Type of batch system running on your server
long: Type of batch system running on your server. Only slurm and torque are supported at this time
group: "execution"
explevel: "easy"
queue:
default: ""
type: string
minchars: 0
maxchars: 100
title: Queue name
short: Name of the batch queue to which jobs will be submitted
long: Name of the batch queue to which jobs will be submitted. If not defined the batch system default will be used.
group: "execution"
explevel: easy
queue_limit:
default: 100
type: integer
min: 1
max: 9999
title: Number of jobs to submit to the batch system
short: Number of jobs to submit to the batch system
long: This parameter controls the number of jobs that will be submitted to the batch system. In combination with the concat parameter this allow to limit the load on the queueing system and also make sure jobs remain in the queue for some time (if concat > 1) to avoid high system loads on the batch system.
group: "execution"
explevel: easy
concat:
default: 1
type: integer
min: 1
max: 9999
precision: 0
title: Number of models to produce per job.
short: Multiple models can be calculated within one job
long:
This defines the number of models that will be generated within on job script.
This allows to concatenate the generation of models into one script.
In that way jobs might run longer in the batch system and reduce the load on the scheduler.
group: "execution"
explevel: easy
self_contained:
default: false
type: boolean
title: Create a self-contained run
short: This option will copy the CNS scripts and executable to the run folder.
long:
This option will copy the CNS scripts and executable to the run folder to ensure that all scripts are available within the run dir.
This can be useful for for example remote execution of a job or for debugging purpose to allow to edit the scripts without touching the
main installation.
group: "execution"
explevel: guru
clean:
default: true
type: boolean
title: Clean the module output files.
short: Clean the module if run succeeds by compressing or removing output files.
long:
When running haddock through the command-line, the 'clean' parameter will
instruct the workflow to clean the output files of the module if the whole
run succeeds. In this process, PDB and PSF files are compressed to gzip,
with the extension `.gz`. While files with extension `.seed`, `.inp`, and
`.out` files are archived, and the original files deleted. The time to
perform a cleaning operation depends on the number of files in the folders
and the size of the files. However, it should not represent a limit step in
the workflow. For example, a rigidbody sampling 10,000 structures takes
about 4 minutes in our servers. This operation uses as many cores as allowed
by the user in the 'ncores' parameter. SSD disks will perform faster by
definition. See also the 'haddock3-clean' and 'haddock3-unpack' command-line
clients.
group: "clean"
explevel: easy
offline:
default: false
type: boolean
title: Isolate haddock3 from internet.
short: Completely isolate the haddock3 run & results from internet.
long: For interactive plots, we are using the plotly library. It can be
embedded as a link to the plotly.js library and fetched from the web,
or directly copied on the html files AT THE COST OF ~3Mb per file.
Setting this parameter to `true` will add the javascript library in
generated files, therefore completely isolating haddock3 from any web call.
group: "execution"
explevel: easy
debug:
default: false
type: boolean
title: Write intermediate and stdout files.
short: Write intermediate and stdout files.
long: When set to true, this option will increase the amount of I/O
operations by writing intermediate input, output and error files on disk.
Turning it to false can be useful for example when running on a network
file system where I/O operations are slow.
group: "execution"
explevel: easy
incompatible:
false:
mode: batch
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