Proceedings of the 2007 Winter Simulation Conference S. G. Henderson, B. Biller, M.-H. Hsieh, J. Shortle, J. D. Tew, and R. R. Barton, eds. OPTIMISTIC PARALLEL DISCRETE EVENT SIMULATION OF THE EVENT-BASED TRANSMISSION LINE MATRIX METHOD David W. Bauer Jr. Ernest H. Page The MITRE Corporation 7525 Colshire Drive McLean, VA 22102, U.S.A. ABSTRACT In this paper we describe a technique for efficient paralleliza- tion of digital wave guide network (DWN) models based on an interpretation of the finite difference time domain (FDTD) method for discrete event simulation. Modeling methodologies based on FDTD approaches are typically constrained in both the spatial and time domains. This interpretation for discrete event simulation allows us to in- vestigate the performance of DWN models in the context of optimistic parallel discrete event simulation employing reverse computation for rollback support. We present par- allel performance results for a large-scale simulation of a 3D battlefield scenario, 100km 2 and at a height of 100m with a resolution of 100m in the X-, Y-planes, and 10m in the Z-plane for 754 simultaneous radio wave transmissions. 1 INTRODUCTION Parallel discrete event simulation (PDES) technology has been employed successfully over the last 30 years to im- prove the performance of many modeling methodologies. Recently, researchers in this field have begun to investigate the efficacy of PDES as applied to modeling physical sys- tems. Common approaches to modeling physical systems include, but are not limited to, ray-tracing and the finite difference time domain (FDTD) methods. However these methods traditionally have not benefitted from discrete event simulation because of constraints in the spatial and time domains, related to each method. For example, the FDTD method is limited by the Courant-Lewy-Friedrichs (CFL) condition (Courant, Friedrichs, and Lewy 1928, Courant, Friedrichs, and Lewy 1967). In the past few years, researchers have begun to adapt these methods to the discrete event paradigm. Notably, a 2005 study applied discrete event simulation to the particle- in-cell (PIC) method (Karimabadi et al. 2005) and achieved a two order of magnitude increase in performance. The PIC method has a long history, reviewed in Birdsall (1991), and is commonly used in the area of plasma physics. The break-through in this approach was the removal of the CFL constraint, which allowed for a two order of magnitude improvement of the runtime. This interpretation was then studied in the context of parallel discrete event simulation by Tang et al. (2006) for a 1D spacecraft model, which improved the performance by an additional order of mag- nitude. In 2006, James Nutaro published a study adapting the FDTD method with respect to digital wave guide network wave simulation to the discrete event paradigm. Here, the focus was on the propagation of electromagnetic waves through a complex 3D environment. A formal description of the algorithm was defined for discrete event systems. Nutaro indicated greater than an order of magnitude improvement in the cost of computation over the FDTD method, for high resolution 3D models of Digital Waveguide Networks (DWN). In this paper we apply the formal model outlined in Nutaro (2006) to the PDES paradigm, specifically optimistic synchronization enabled by reverse computation. We chose this method to study because the algorithm allowed for reso- lutions independent of the wavelength of the electromagnetic waves modeled. Our challenge is to apply this method to a DWN physical simulation for battlefield scenarios where the scale of the environment (100km long X 100km wide X 100m in height) is large and where the number of radio wave transmissions is large, in this case 754 simultaneous wave transmissions. The main contribution of our work is the application of the Event-Based Transmission Line Matrix (ETLM) mod- eling method to the area of PDES known as optimistic simulation. Optimistic synchronization was first proposed by Jefferson (1985) and allows as fast as possible event execution where violations of the causality constraint may occur. Where violations occur, the causality constraint is then preserved by rolling back improperly processed events, 676 1-4244-1306-0/07/$25.00 ©2007 IEEE