问题描述
要尝试，我（不久前）执行康威的生命游戏（我知道的的相关问题！）。
To experiment, I've (long ago) implemented Conway's Game of Life (and I'm aware of this related question!).
我的执行情况保持2阵列布尔值，再presenting了最后的状态的工作，而状态更新（2个阵列被交换在每次迭代）。虽然这是相当快的，我经常在想，如何来优化它。
My implementation worked by keeping 2 arrays of booleans, representing the 'last state', and the 'state being updated' (the 2 arrays being swapped at each iteration). While this is reasonably fast, I've often wondered about how to optimize this.
一种想法，例如，将是precompute在迭代n了所述区域可以的在迭代被修改（N + 1）（因此，如果一个小区不属于此类一个区域，它甚至不会被考虑修饰迭代（N + 1））。我知道，这是非常模糊的，我从来没有花时间去详谈......
One idea, for example, would be to precompute at iteration N the zones that could be modified at iteration (N+1) (so that if a cell does not belong to such a zone, it won't even be considered for modification at iteration (N+1)). I'm aware that this is very vague, and I never took time to go into the details...
你有什么想法（或经验！）如何去优化（速度）的生命迭代游戏？
Do you have any ideas (or experience!) of how to go about optimizing (for speed) Game of Life iterations?
推荐答案
我会从另一个问题引用我的答案，因为我提的章节有一些非常有趣和微调的解决方案。一些实施细节在C和/或组件，是的，但在大多数情况下的算法，可以用任何语言工作：
I am going to quote my answer from the other question, because the chapters I mention have some very interesting and fine-tuned solutions. Some of the implementation details are in c and/or assembly, yes, but for the most part the algorithms can work in any language:
章节 17 和的的 迈克尔Abrash的Graphics 程序员黑皮书是一 最有趣的读取我曾经 了。这是思维的教训 外箱。全书 确实很大，但最终的优化 解决方案，以生命的游戏是 编程不可思议位。
这篇关于优化Conway的“生命游戏”的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！