2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation (2002)
May 12, 2002 to May 15, 2002
Christopher D. Carothers , Rensselaer Polytechnic Institute
Of critical importance to any real-time system is the issue of predictability. We divide overall system predictability into two parts: algorithmic and systemic. Algorithmic predictability is concerned with ensuring that the parallel simulation engine and model from a complexity point of view are able to consistently yield results within a real-time deadline. Systemic predictability is concerned with ensuring that OS scheduling, interrupts and virtual memory overheads are consistent over a real-time period. To provide a framework for investigating systemic predictability, we define a new class of parallel simulation called Extreme Simulation or XSim. An XSim is any analytic parallel simulation that is able to generate a statistically valid result by a real-time deadline. Typically, this deadline is between 10 and 100 milliseconds. XSims are expected to provide decision support to existing complex, real-time systems. As a new design and implementation methodology for realizing XSims, we embed a state-of-the-art optimistic simulator into the Linux operating system. In this operating environment, OS scheduling and interrupts are disabled. Given a 50 millisecond model completion deadline, we observe that the XSim has a systemic predictability, measure of 98\% compared with only 56\% for the same Time Warp system operating in user-level.
xsim, real-time, predictability, time warp, parallel simulation
Christopher D. Carothers, "XSim: Real-Time Analytic Parallel Simulations", 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation, vol. 00, no. , pp. 27, 2002, doi:10.1109/PADS.2002.1004197