Network researchers today are unable to test their new ideas at scale before deployment due to the prohibitive costs of custom testbeds and the slow speed of large-scale network simulators. Data center simulation is particularly slow because of the massive amount of bandwidth and high degree of redundant computation incurred in simulating the network stacks of thousands of commodity machines. By using approximation to replace redundant portions of the simulation, we improve computation time while retaining high accuracy.