Developing parallel, discrete event simulations in Python - first results and user experiences with the SimX library

This paper describes SimX, a recently developed library for developing parallel, discrete-event simulations in Python. Written in C++ and Python, SimX enables rapid development and prototyping of a parallel simulation entirely in Python by providing the simulation modeler with core functionality such as processes, event queuing, time advancement, domain partitioning, synchronization and message passing. Designed for both ease-of-use and scalability, applications built using SimX can be executed on multi-core workstations or high performance clusters and can also be easily integrated with other Python tools for scientific computing. In this paper, we briefly discuss the motivation for developing SimX, provide a brief but illustrative example on using SimX to develop an application, a short description of its architecture and some of our initial experiences using SimX in a diverse array of domains. SimX is free software and is publicly available at http://github.com/sim-x under the GNU LGPL license.