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⇤ ← Revision 39 as of 2016-05-03 13:21:45 →
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Editor: JendrikSeipp
Comment: Add instructions for experiments on Maia. Lab docs include installation info for benchmarks and VAL, but rtfd.org is slow to build the new version...
← Revision 41 as of 2018-04-13 15:00:59 → ⇥
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Editor: JendrikSeipp
Comment:
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We recommend using the {{{downward}}} package for running Fast Downward experiments. It is part of {{{lab}}}, a python library for running code on large benchmark sets. Experiments can be run either locally or on a computer cluster. You can find the code at https://bitbucket.org/jendrikseipp/lab. The documentation is available at http://lab.rtfd.org. We recommend using the {{{Downward Lab}}} toolkit for running Fast Downward experiments. Experiments can be run either locally or on a computer cluster. You can find the code at https://bitbucket.org/jendrikseipp/lab. The documentation is available at http://lab.rtfd.org.
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== Experiments on Maia (AI-Basel grid) == == AI Basel Grid ==
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Please follow the instructions in the [[https://lab.readthedocs.io/en/latest/downward.tutorial.html|downward tutorial]] to install the necessary components.

The components need some environment variables and program modules. Here is an example ''~/.profile'' file (from May 2016):

{{{#!highlight bash
export PATH=${PATH}:~/bin # You can put the "validate" executable here
export PYTHONPATH="~/lib/python/lab:~/lib/cplex/CPLEX_Studio/cplex/python/x86-64_sles10_4.1/"

export DOWNWARD_CPLEX_INCDIR=~/lib/cplex/cplex/include/ilcplex
export DOWNWARD_CPLEX_LIBDIR=~/lib/cplex/cplex/lib/x86_sles10_4.1/static_pic
export DOWNWARD_CPLEX_ROOT=~/lib/cplex/cplex
export DOWNWARD_COIN_ROOT=~/lib/coin

module purge
module -q load Mercurial/2.5.2-goolf-1.4.10-Python-2.7.5 # Also loads Python 2.7
module -q load Clang/3.3-GCC-4.8.2 # Also loads GCC 4.8
module -q load CMake/2.8.11-GCC-4.8.2
}}}		 Please see https://wiki.dmi.unibas.ch/doku.php?id=fbi:ai:compute-cluster (only available from within the University of Basel network) for instructions on how to use the AI Basel grid.

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Experiments

We recommend using the Downward Lab toolkit for running Fast Downward experiments. Experiments can be run either locally or on a computer cluster. You can find the code at https://bitbucket.org/jendrikseipp/lab. The documentation is available at http://lab.rtfd.org.

AI Basel Grid

Please see https://wiki.dmi.unibas.ch/doku.php?id=fbi:ai:compute-cluster (only available from within the University of Basel network) for instructions on how to use the AI Basel grid.