Gurobi

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.

License limitations

Compute Canada supports and provides a free license to use Gurobi on the Graham, Cedar, Béluga 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).

Configuring your account

You do NOT need to create a ~/.licenses/gurobi.lic file. The required settings to use the Compute Canada Gurobi license are configured by default when you load a gurobi module on any cluster. To verify your username has been added to the Compute Canada Gurobi license and is working properly run the following command. If it returns "Fail" then please contact support to request help.

$ module load gurobi
$ gurobi_cl 1> /dev/null && echo Success || echo Fail

Interactive Allocations

Gurobi Command-Line Tools

[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

Replaying API calls

You can record API calls and repeat them with command

[gra800:~] gurobi_cl recording000.grbr

Reference: 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 --account=def-group   # some account
#SBATCH --time=0:30           # time limit (D-HH:MM)
#SBATCH --mem-per-cpu=1000M   # memory per CPU (in MB)

# use a version >= 9.0.3 
module load StdEnv/2020
module load gurobi/9.1.0

# 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 --account=def-group   # some account
#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)

# use a version <= 9.0.2 
module load StdEnv/2016.4     # or StdEnv/2018.3
module load gurobi/9.0.2

# 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. For example compare the python versions supported by the gurobi 8.11 and 9.0.1 modules:

[name@server ~] $ module load StdEnv/2016  (not needed for gurobi>9.0.2)
[name@server ~] $ module load gurobi/8.1.1
[name@server ~] $ cd $EBROOTGUROBI/lib
[name@server ~] $ ls -d python*
  python2.7        python2.7_utf32    python2.7_utf16
  python3.5_utf32  python3.6_utf32    python3.7_utf32

[name@server ~] $ module load StdEnv/2016  (not needed for gurobi>9.0.2)
[name@server ~] $ module load gurobi/9.0.1
[name@server ~] $ cd $EBROOTGUROBI/lib
[name@server ~] $ ls -d python*
  python3.7        python2.7_utf16  python2.7_utf32
  python3.5_utf32  python3.8_utf32  python3.6_utf32  python3.7_utf32

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).

Creating the virtual environment

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. The following steps need to be done only once per system. First load the modules to 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 install the Python packages we want to use, in this case pandas for example:

(env_gurobi) [name@server ~] $ pip install --no-index  pandas
  Ignoring pip: markers 'python_version < "3"' don't match your environment
  Looking in links:
  /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/nix/avx2
  /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/nix/generic
  /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic
  Collecting pandas,
  Collecting numpy>1.13.3 (from pandas)
  [...]
  Successfully installed numpy-1.18.4 pandas-1.0.3 python-dateutil-2.8.1 pytz-2020.1 six-1.15.0

The third and final 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

Using the virtual environment

Python scripts can now import both Pandas and Gurobi:

[name@server ~] $ cat my_gurobi_script.py
  import pandas as pd
  import numpy as np
  import gurobipy as gurobi
  from gurobipy import *
  etc

Once created we can activate our Gurobi environment at any time with:

[name@server ~] $ module load gurobi/9.0.1
  source ~/env_gurobi/bin/activate
  (env_gurobi) python my_gurobi_script.py

Note that we now use python instead of gurobi.sh! 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 load StdEnv/2016.4
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

Using Gurobi with Jupyter notebooks

Various topics can be found by visiting support.gurobi.com and searching for Jupyter notebooks. "The article titled Where can I learn more about building optimization models?" provides several examples. Information specific to using Gurobi with Jupyter notebooks on Compute Canada systems will be added to this wiki section in the future as required.

Cite Gurobi

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