- Getting started
- First steps
- The prototypes
- The Tasks
- Composing Samplings
- The Samplings
- The Domains
- The Factors
- The Environments
- The Hooks
- The Sources
Need to evaluate the effect of some parameters on your program?
Need to execute your program againts many datasets?
Need to calibrate?
Need to optimize?
OpenMOLE (Open MOdeL Experiment) makes it simple to distribute your parallel experiments on distributed computing environments. If you want to execute the same program for many different inputs (parameters or datasets), OpenMOLE is the tool that you need. The typical usage of OpenMOLE are high performance model calibration, model exploration, machine learning, optimization, data processing.
- Expressive – Graphical and scripted workflow system to describe your naturally parallel processes.
- Distributed computing – Works with your multi-core machines, desktop room, clusters, grids.
- Works with your programs – Java, Binary exe, NetLogo, R, Scilab, Python, C++…
- Scalable – Handles millions of tasks and GBs of data.
- Model analysis – Design of experiments, stochastic model replication, calibration, sensitivity analysis…
- Mature – Developed since 2008 and widely used.