ACM Transactions on Programming Languages and Systems (TOPLAS)
Algorithms for Scheduling Imprecise Computations
Computer - Special issue on real-time systems
MIDAS: Integrated Design and Simulation of Distributed Systems
IEEE Transactions on Software Engineering
Time Warp simulation in time constrained systems
PADS '93 Proceedings of the seventh workshop on Parallel and distributed simulation
PORTS: a parallel, optimistic, real-time simulator
PADS '94 Proceedings of the eighth workshop on Parallel and distributed simulation
GTW: a time warp system for shared memory multiprocessors
WSC '94 Proceedings of the 26th conference on Winter simulation
PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
Computing global virtual time in shared-memory multiprocessors
ACM Transactions on Modeling and Computer Simulation (TOMACS)
The threshold of event simultaneity
Transactions of the Society for Computer Simulation International - Special issue on parallel and distributed simulation
ROSS: a high-performance, low memory, modular time warp system
PADS '00 Proceedings of the fourteenth workshop on Parallel and distributed simulation
Efficient optimistic parallel simulations using reverse computation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Looking ahead of real time in Hybrid component networks
Proceedings of the fifteenth workshop on Parallel and distributed simulation
Practical parallel simulation applied to aviation modeling
Proceedings of the fifteenth workshop on Parallel and distributed simulation
Real-Time Systems
Data Organization and Data Comparison for Model Validation in Faster-than-Real-Time Simulation
ANSS '06 Proceedings of the 39th annual Symposium on Simulation
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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.