Eindhoven University of Technology
Genetic algorithms are commonly used for automatically solving complex design problem because exploration using genetic algorithms can consistently deliver good results when the algorithm is given a long enough run-time. However, the exploration time for problems with huge design spaces can be very long, often making exploration using a genetic algorithm practically infeasible. In this paper, the authors present a genetic algorithm for exploring the instruction-set architecture of VLIW ASIPs and demonstrate its effectiveness by comparing it to two heuristic algorithms. They present several optimizations to the genetic algorithm configuration, and demonstrate how caching of intermediate compilation and simulation results can reduce the exploration time by an order of magnitude.