In this paper, we propose a novel parallel state justification tool, GACO, utilizing Ant Colony Optimization (ACO) on Graphical Processing Units (GPU). With the high degree of parallelism supported by the GPU, GACO is capable of launching a large number of artificial ants to search for the target state. A novel parallel simulation technique, utilizing partitioned navigation tracks as guides during the search, is proposed to achieve extremely high computation efficiency for state justification. We present the results on a GPU platform from NVIDIA (a GeForce GTX 285 graphics card) that demonstrate a speedup of up to 228× compared to deterministic methods and a speedup of up to 40× over previous state-of-the-art heuristic based serial tools.
['Min Li', 'Kelson Gent', 'Michael S. Hsiao']
Utilizing GPGPUs for design validation with a modified Ant Colony Optimization