Performance and energy efficiency analysis of a Reversi player for FPGAs and General Purpose Processors

Board-game applications are frequently found in mobile devices where the computing performance and the energy budget are constrained. Since the Artificial Intelligence techniques applied in these games are computationally intensive, the applications developed for mobile systems are frequently simplistic, far from the level of equivalent applications developed for desktop computers.Currently board games are software applications executed on General Purpose Processors. However, they exhibit a medium degree of parallelism and a custom hardware accelerator implemented on an FPGA can take advantage of that.We have selected the well-known Reversi game as a case study because it is a very popular board game with simple rules but huge computational demands. We developed and optimized software and hardware designs for this game that apply the same classical Artificial Intelligence techniques. The applications have been executed on different representative platforms and the results demonstrate that the FPGAs implementations provide better performance, lower power consumption and, therefore, impressive energy savings. These results demonstrate that FPGAs can efficiently deal with this kind of problems.