Gurobi/fr

Gurobi is a commercial software suite for solving complex optimization problems. This page wiki page describes the non-commercial use of Gurobi software on Compute Canada clusters and is currently a work in progress.

Limites de la licence

Compute Canada supports and provides a free license to use Gurobi on the Graham, Cedar, Beluga and Niagara clusters. The license provides a total number of 4096 simultaneous uses (tokens in use) and permits distributed optimization with up to 100 nodes. A single user can run multiple simultaneous jobs. In order to use Gurobi you must agree to certain conditions. Please contact support and include a copy of the following completed Academic Usage Agreement. You will then be added into the Compute Canada license file as a permitted user within a few days:

Academic Usage Agreement

My Compute Canada username is "_______" and I am a member of the academic institution "_____________________".  This message confirms that I will only use the Compute Canada Gurobi license provided on Compute Canada systems for the purpose of non-commercial research project(s) to be published in publicly available article(s).

Allocations initeractives

Ligne de commande

[gra-login2:~] salloc --time=1:00:0 --cpus-per-task=8 --mem=1G --account=def-xyz
[gra800:~] module load gurobi
[gra800:~] gurobi_cl Record=1 Threads=8 Method=2 ResultFile=p0033.sol LogFile=p0033.log $GUROBI_HOME/examples/data/p0033.mps
[gra800:~] gurobi_cl --help

Gurobi Interactive Shell

[gra-login2:~] salloc --time=1:00:0 --cpus-per-task=8 --mem=1G --account=def-xyz
[gra800:~] module load gurobi
[gra800:~] echo "Record 1" > gurobi.env    see *
[gra800:~] gurobi.sh
gurobi> m = read('/cvmfs/restricted.computecanada.ca/easybuild/software/2017/Core/gurobi/8.1.1/examples/data/glass4.mps') 
gurobi> m.Params.Threads = 8               see **
gurobi> m.Params.Method = 2
gurobi> m.Params.ResultFile = "glass4.sol"
gurobi> m.Params.LogFile = "glass4.log"
gurobi> m.optimize()
gurobi> m.write('glass4.lp')
gurobi> m.status                           see ***
gurobi> m.runtime                          see ****
gurobi> help()

where

   * https://www.gurobi.com/documentation/8.1/refman/recording_api_calls.html
  ** https://www.gurobi.com/documentation/8.1/refman/parameter_descriptions.html
 *** https://www.gurobi.com/documentation/8.1/refman/optimization_status_codes.html
**** https://www.gurobi.com/documentation/8.1/refman/attributes.html

Replay API Call Recording

[gra800:~] gurobi_cl recording000.grbr

Référence: https://www.gurobi.com/documentation/8.1/refman/recording_api_calls.html

Batch Jobs

Model in LP-format

This is an example job script for an optimization model written in the LP format.

File : gurobi_example.sh

#!/bin/bash
#SBATCH --time=0:30           # time limit (D-HH:MM)
#SBATCH --mem-per-cpu=1000M   # memory per CPU (in MB)
module purge  
module load gurobi

# Create environment file in current directory setting the number of threads:
echo "Threads ${SLURM_CPUS_ON_NODE:-1}" > gurobi.env

gurobi_cl ${GUROBI_HOME}/examples/data/coins.lp

Job using Gurobi Python

This is an example jobscript for a model using Gurobi-Python.

File : gurobi-py_example.sh

#!/bin/bash
#SBATCH --time=0-00:30        # time limit (D-HH:MM)
#SBATCH --cpus-per-task=1     # number of CPUs (threads) to use
#SBATCH --mem-per-cpu=1000M   # memory per CPU (in MB)
module purge  
module load gurobi

# Create environment file in current directory setting the number of threads:
echo "Threads ${SLURM_CPUS_ON_NODE:-1}" > gurobi.env

gurobi.sh  ${GUROBI_HOME}/examples/python/facility.py

Using Gurobi in Python virtual environments

Gurobi brings it's own version of Python but that one does not contain any 3rd-party Python packages except Gurobi. In order to use Gurobi together with popular Python packages like NumPy, Matplotlib, Pandas and others, we need to create a virtual Python environment in which we can install both gurobipy and e.g. pandas.

Before we start, we need to decide which combination of versions for Gurobi and Python to use.

[name@server ~] $ module load gurobi/8.1.1
[name@server ~] $ cd $EBROOTGUROBI/lib
[name@server ~] $ ls -dF python*
  python2.7/        python2.7_utf32/  python3.6_utf32/
  python2.7_utf16/  python3.5_utf32/  python3.7_utf32/
[name@server ~] $ module load gurobi/9.0.1
[name@server ~] $ cd $EBROOTGUROBI/lib
[name@server ~] $ ls -dF python*
  python2.7_utf16/  python3.5_utf32/  python3.7/        python3.8_utf32/
  python2.7_utf32/  python3.6_utf32/  python3.7_utf32/
[name@server ~] $ cd

We see that gurobi/8.1.1 brings it's own installation of python2.7/ and Python packages for Python 2.7, 3.5, 3.6 and 3.7 (pythonX.Y_utf32/), while gurobi/9.0.1 by default uses python3.7/ and brings Python packages for Python 2.7, 3.5, 3.6, 3.7 and 3.8 (pythonX.Y_utf32/).

In this example we want to create a Python environment based on python/3.7 in which we want to use gurobi/9.0.1 and install the Pandas package.

Créer un environnement virtuel Python

These steps need to be done only once per system.

The first step is to load the modules, create the virtual environment and activate it.

[name@server ~] $ module load gurobi/9.0.1 python/3.7
[name@server ~] $ virtualenv --no-download  ~/env_gurobi
  Using base prefix '/cvmfs/soft.computecanada.ca/easybuild/software/2017/Core/python/3.7.4'
  New python executable in /home/name/env_gurobi/bin/python
  Installing setuptools, pip, wheel...
  done.
[name@server ~] $ source ~/env_gurobi/bin/activate

Now that the environment has been activated we can install the Python packages we want to use, in this case pandas.

The third step is to install gurobipy into the environment:

(env_gurobi) [name@server ~] $ cd $EBROOTGUROBI
(env_gurobi) [name@server ~] $ python setup.py build --build-base /tmp/${USER} install
  running build
  running build_py
  creating /tmp/name
  creating /tmp/name/lib
  creating /tmp/name/lib/gurobipy
  copying lib/python3.7_utf32/gurobipy/__init__.py -> /tmp/name/lib/gurobipy
  copying lib/python3.7_utf32/gurobipy/gurobipy.so -> /tmp/name/lib/gurobipy
  running install
  running install_lib
  creating /home/name/env_gurobi/lib/python3.7/site-packages/gurobipy
  copying /tmp/name/lib/gurobipy/gurobipy.so -> /home/name/env_gurobi/lib/python3.7/site-packages/gurobipy
  copying /tmp/name/lib/gurobipy/__init__.py -> /home/name/env_gurobi/lib/python3.7/site-packages/gurobipy
  byte-compiling /home/name/env_gurobi/lib/python3.7/site-packages/gurobipy/__init__.py to __init__.cpython-37.pyc
  running install_egg_info
  Writing /home/name/env_gurobi/lib/python3.7/site-packages/gurobipy-9.0.1-py3.7.egg-info
(env_gurobi) [name@server ~] $ cd

Using the Gurobi-enabled virtual environment

Python scripts can now import both Pandas and Gurobi:

import pandas as pd
import numpy as np
import gurobipy as gurobi
from gurobipy import *
# [...]

Once created we can activate Gurobi and the environment with:

module load gurobi/9.0.1
source ~/env_gurobi/bin/activate
python  my_gurobi_script.py

Remarquez que nous utilisons maintenant python plutôt que gurobi.sh.

And this is an example job script that we can use:

File : gurobi-py_example.sh

#!/bin/bash
#SBATCH --time=0-00:30        # time limit (D-HH:MM)
#SBATCH --cpus-per-task=1     # number of CPUs (threads) to use
#SBATCH --mem-per-cpu=1000M   # memory per CPU (in MB)
module purge
module load gurobi/9.0.1
source ~/env_gurobi/bin/activate

# Create environment file in current directory setting the number of threads:
echo "Threads ${SLURM_CPUS_ON_NODE:-1}" > gurobi.env

python  my_gurobi_script.py

Cite Gurobi

Please see How do I cite Gurobi software for an academic publication?