Multi-objective Probabilistic Model Checking built on a C++ API of Storm. This project is built on the Storm project and to use it, Storm model checker needs to be build from source with all dependencies. See Storm for installation details.

This build is known to work on Ubuntu 20.04 LTS. Other linux flavours are possible however dependency setup can be tricky.

Before starting, make sure that Storm and all of its dependencies are installed is installed. If not, see the documentation.

This project uses cmake which should be bundled with Ninja. If Ninja is available you will be able to make use of the convenient configurations and build script.

This project requires CUDA Toolkit 12.xx and the associated NVIDIA driver 525+. This cuda toolkit is essential as it provides 64bit numeric types for the GPU and provides more modern sparse matrix multiplication algorithms from Nvidia CuSparse. If installed correctly, using the command nvidia-smi you should see something like:

+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.113.01             Driver Version: 535.113.01   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|

A further note on setting up your environment.

Cuda Toolkit has a mandatory action of adding the toolkit to the PATH variable. Add the following to .bashrc or .profile:

export PATH=/usr/local/cuda-12.2/bin${PATH:+:${PATH}}

Additionally, if you develop in an IDE which builds based off cmake, such as CLion, then you will also need to set the LD_LIBRARY_PATH to contain the toolkit's lib64 directory. This can also be added to .bashrc or .profile.

export LD_LIBRARY_PATH=/usr/local/cuda-12.2/lib64 ${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

This avoids errors by the IDE debug compiler relating to setting CMAKE_CUDA_ARCHITECTURES.

If your IDE cannot find the Storm header files, you can specify the header search paths so that the Storm source directories can be indexed (see Manage CMake project files). This can be done by adding the following line into the current CMakeList.txt file:

set(storm_INCLUDE_DIR, ./storm)

where storm is a symlink to <YOUR_STORM_ROOT_DIRECTORY>/build/src/storm created in the project root.

First, clone and cd into the project then configure and compile the project. Execute

mkdir build
./configure.sh
./build.sh

To test your build is working, run the executable using the convenience script:

./run.sh

This project only computes multi-objective model checking of convex queries.

src/main.cpp is the entry point of the project.

The first call is to mopmc::check which parses a model as a Prism model along with properties from a .pctl file. These are argument inputs with the first being model and the second being property inputs.

Model parsing is done using Storm parsing methods and once done multi-objective model checking is done by calling:

mopmc::multiobjective::performMultiObjectiveModelChecking(env, *mdp, formulas[0]->asMultiObjectiveFormula());

This class method first preprocesses the multi-objective formulas and model by calling methods in

src/mopmc-src/model-checking/MultiObjectivePreprocessor.cpp(h)

After model construction is complete, MOPMC model checking is conducted using the methods and classes in src/mopmc-src/model-checking/MOPMCModelChecking.cpp(h). The class often makes reference to the solvers both c++ and CUDA based located in src/mopmc-src/solvers.