Section Conclusions Sample Clauses

Section Conclusions. ‌ We have performed an in-depth scalability study of both Tree and Root Parallelizations of the MCTS algorithm on the Xeon CPU and the Xeon Phi for the game of Hex. It is the first large-scale (up to 240 threads and 61 cores) study of Tree Parallelization on a real shared-memory many-core machine. Contrary to previous results [EM10], we show that the effect of using data locks is not a limiting factor on the performance of a Tree Parallelization for 16 threads on the Xeon CPU and 64 threads on the Xeon Phi. To understand the reason for this low performance we performed a detailed xxx- ing analysis to find out where the most time of the algorithm has been spent in the selection step, expansion step, playout step, or update step. For the Hex board size of 11 × 11, MCTS spends most of its time in the playout phase. This phase of the algorithm is problem dependent, for example, it is different for Go and Hex; the dif- xxxxxxx is even different for distinct board sizes. In our program, around 80% of the total execution time for performing a move is spent in the playout phase. Since the playout phase dominates execution time of each thread, the Xeon CPU outperforms the Xeon Phi significantly because of more powerful cores. No method for vectorization has been devised for the playout phase. Therefore, for the current ratio of Xeon CPU cores versus Xeon Phi cores (24 versus 61), it is not possible to reach the same performance on the Xeon Phi because each core of the Xeon CPU is more powerful than each core of the Xeon Phi for sequential execution. From these results, we may conclude that for the current ratio of Xeon CPU cores versus Xeon Phi cores, the parallel MCTS algorithms for games such as Hex or Go on the Xeon Phi have a limitation. Therefore, it is interesting to investigate the limitation problem in the other domains in which MCTS has been successful such as those mentioned in [vdHPKV13].
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