A developer has released Cimba, an open-source C library for discrete event simulation (DES) that claims significant performance gains over Python-based tools.
The library uses stackful coroutines and multithreading to achieve what its creator reports as 45x faster execution than SimPy, the dominant Python DES framework. The project carries an Apache-2.0 license and minimal GitHub traction so far: two stars, no forks.
Discrete event simulation models systems as sequences of discrete events over time, common in manufacturing logistics, telecommunications networks, and increasingly in autonomous vehicle validation and blockchain performance testing. The performance gap matters when simulation runtime becomes a development bottleneck.
Python's SimPy and similar tools (Salabim, Simian) face inherent interpreter overhead. Enterprise alternatives like AnyLogic offer visual modeling but come with licensing costs. Cimba positions itself as a high-performance foundation for custom simulation engines where C's execution speed justifies the development complexity trade-off.
The approach mirrors patterns elsewhere in the simulation space. Devastator, a C++ parallel DES engine from 2023, demonstrated 5x speedup over ROSS at scale (32,000+ cores). SIMBA, a blockchain simulator, achieved 30x efficiency gains using Merkle trees for block verification.
What this means in practice: teams running thousands of simulation iterations, particularly in APAC manufacturing and telco sectors, may find C-based engines reduce evaluation time from hours to minutes. The real question is whether the performance gain justifies moving from Python's rapid prototyping to C's development overhead.
History suggests niche adoption. Python DES tools remain dominant for quick modeling despite performance limitations. Cimba will likely find use where simulation is production-critical, not exploratory: think autonomous vehicle test suites running millions of scenario permutations, or network capacity planning at carrier scale.
The project documentation is live at cimba.readthedocs.io. We'll see if enterprise teams with serious performance requirements adopt it, or if Python's ecosystem convenience keeps them accepting slower execution.