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DESCRIPTION

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Description: As a successor of the packages BatchJobs and BatchExperiments,
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batchtools provides a parallel implementation of the Map function
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for high performance computing systems managed by schedulers (IBM LSF
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<http://www-03.ibm.com/systems/spectrum-computing/products/lsf/>,
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OpenLava <http://www.openlava.org/>, Univia Grid Engine
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<http://www.univa.com/> (formerly Sun Grid Engine and Oracle Grid Engine),
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Slurm <http://slurm.schedmd.com/>, Torque/PBS
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<http://www.adaptivecomputing.com/products/open-source/torque/>, and Docker
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Swarm <https://docs.docker.com/swarm/>).
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for high performance computing systems managed by schedulers: IBM Spectrum
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LSF (<http://www-03.ibm.com/systems/spectrum-computing/products/lsf/>),
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OpenLava (<http://www.openlava.org/>), Univia/Oracle/Sun Grid Engine
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(<http://www.univa.com/>), Slurm (<http://slurm.schedmd.com/>), Torque/PBS
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(<http://www.adaptivecomputing.com/products/open-source/torque/>), and
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Docker Swarm (<https://docs.docker.com/swarm/>).
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A multicore and socket mode allow the parallelization on a local machines,
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and multiple machines can be hooked up via SSH to create a makeshift cluster.
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Moreover, the package provides an abstraction mechanism to define
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and multiple machines can be hooked up via SSH to create a makeshift
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cluster. Moreover, the package provides an abstraction mechanism to define
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large-scale computer experiments in a well-organized and reproducible way.
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License: LGPL-3
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URL: https://github.com/mllg/batchtools
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URLNote: https://github.com/mllg/batchtools
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BugReports: https://github.com/mllg/batchtools/issues
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NeedsCompilation: yes
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ByteCompile: yes

README.md

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As a successor of the packages [BatchJobs](https://github.com/tudo-r/BatchJobs) and [BatchExperiments](https://github.com/tudo-r/Batchexperiments), batchtools provides a parallel implementation of Map for high performance computing systems managed by schedulers like Slurm, Torque, or SGE.
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Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
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The development is still in beta.
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## Installation
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Install via [devtools](https://cran.r-project.org/package=devtools):
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Install the development version via [devtools](https://cran.r-project.org/package=devtools):
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```{R}
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devtools::install_github("mllg/batchtools")
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```

docs/articles/ErrorHandling.html

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docs/articles/ExampleExperiment.html

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docs/articles/Setup.html

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docs/index.html

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docs/reference/ExperimentRegistry.html

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docs/reference/JobCollection.html

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