Evaluating Root Parallelization in Go
Evaluating Root Parallelization in Go
复制标题
评估 Go 中的根并行化
DOI：
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发表时间：
2010
影响因子：
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通讯作者：
O. Watanabe
中科院分区：
文献类型：
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作者：
Yusuke Soejima;Akihiro Kishimoto;O. Watanabe
并行蒙特卡罗树搜索(MCTS)被认为是提高计算机围棋程序强度的一种方法。本文分析了两种根并行化方法的性能：基于平均选择的标准策略和基于多数投票的新策略。作为开始代码库，我们使用了Fuego，这是可用的最好的程序之一。我们在处理器核上的实验结果表明，多数投票的性能优于平均选择。此外，我们通过广泛的分析表明，根并行是有局限性的。
Parallelizing Monte Carlo tree search (MCTS) has been considered to be a way to improve the strength of Computer Go programs. In this paper, we analyze the performance of two root parallelization methods: the standard strategy based on average selection and our new strategy based on majority voting. As a starting code base, we used Fuego, which is one of the best programs available. Our experimental results with 64 central processing unit (CPU) cores show that majority voting outperforms average selection. Additionally, we show through an extensive analysis that root parallelization has limitations.