  Lava emplacement is a complex physical phenomenon, affected by several
factors. These include, but are not limited to features of the terrain, the
lava settling process, the effusion rate or total erupted volume, and the
probability of effusion from different locations. One method, which has been
successfully employed to predict lava flow emplacement and forecast the
inundated area and final lava thickness, is the MrLavaLoba method from Vitturi
et al. The MrLavaLoba method has been implemented in their code of the same
name. Here, we introduce Flowy, a new computational tool that implements the
MrLavaLoba method in a more efficient manner. New fast algorithms have been
incorporated for all performance critical code paths, resulting in a complete
overhaul of the implementation. When compared to the MrLavaLoba code, Flowy
exhibits a significant reduction in runtime -- between 100 to 400 times faster
-- depending on the specific input parameters. The accuracy and the
probabilistic convergence of the model outputs are not compromised, maintaining
high fidelity in generating possible lava flow paths and deposition
characteristics. We have validated Flowy's performance and reliability through
comprehensive unit-testing and a real-world eruption scenario. The source code
is freely available on GitHub, facilitating transparency, reproducibility and
collaboration within the geoscientific community.
