SimGrid

SimGrid

Initial release	1998 (1998)[1]
Stable release	3.36 / September 9, 2024; 2 months ago (2024-09-09)[2]
Repository	https://framagit.org/simgrid/simgrid
Written in	Core: C++; Bindings: Python, .[3]
Platform	Unix, Mac OS X, Microsoft Windows
Type	Distributed system simulator, Network simulator, Model Checking
License	GNU Lesser General Public License[3]
Website	simgrid.org

SimGrid is a framework for developing simulators of distributed applications targeting distributed platforms, which can in turn be used to prototype, evaluate and compare relevant platform configurations, system designs, and algorithmic approaches. It provides ready to use models and APIs to simulate popular distributed computing platforms (commodity clusters, wide-area and local-area networks, peers over DSL connections, data centers, etc.)

As a result, SimGrid has served as the foundational technology for developing simulators and obtaining experimental results for a wide range of distributed computing domains: Grids, P2P computing, Cloud, Fog computing, Volunteer computing, HPC with MPI, or MapReduce.

SimGrid is:

• Accurate: SimGrid's simulation models have been theoretically and experimentally evaluated and validated
• Scalable: SimGrid's simulation models and their implementations are fast and have low memory footprint, making is possible to run SimGrid simulations quickly on a single machine
• Usable: SimGrid is free software (LGPL license) available on Linux / Mac OS X / Windows, and allows users to write simulators in C++, C, or Python.

For the last 25 years SimGrid has supported the research in hundreds of scientific publications. Its international user community counts hundred of enthusiastic members around the globe, many of who actively contribute to the SimGrid software directly or indirectly.

• BIGSIM

• SimGrid - official project homepage
• Reference publication: H. Casanova, A. Giersch, A. Legrand, M. Quinson, and F. Suter, “Versatile, Scalable, and Accurate Simulation of Distributed Applications and Platforms,” Journal of Parallel and Distributed Computing, vol. 74, no. 10, pp. 2899 – 2917, 2014.