A Genetic Algorithm for Optimistic Digital Logic Simulation

In this paper, we describe a distributed dynamic load balancing algorithm for parallel optimistic gate level simulation. Our optimistic simulator is based on Time Warp. The load balancing algorithm makes decisions based on the processing and communication loads at each processor. At the core of the algorithm is a genetic algorithm which is used to determine the values of the tuning parameters associated with the algorithm. It also determines the size of the time window of the simulator. The time window is a mechanism used to control the level of optimism of an optimistic simulator in order to avoid excessive rollbacks. An important feature of the genetic algorithm is that it is on-line, i.e. it is executed during the course of the simulation. The genetic algorithm is executed in one processor while the other processors execute the simulation and the load balancing algorithm. Experimental results have indicated a significant decrease in the execution time of the simulationup to a 70% decrease in the simulation time of an optimistic simulator.