Emad Omara's parallel merge sort algorithm assumes that you will have full access to the machine's CPUs for the duration of the sorting operation.
Emad Omara的并行合并排序算法假设了在排序操作的过程中(操作者)对计算机的所有CPU具有完全的访问权限。
Merge-sort is not an inherently parallel algorithm, as it can be done sequentially, and is popular when the data set is too large to fit in memory and must be sorted in pieces.
合并排序本身并非并行算法,因为它可以顺序执行。 当数据集太大,内存无法容纳,必须分片保存的时候,经常使用合并排序。
Use merge sort, in a binary search algorithm complexity: nlogn, n number two together, if can equal to a specific number m, the output yes, otherwise no output.
说明:运用归并排序,在用二分法查找,算法复杂度:nlogn,n个数两两相加,若能等于特定数m,则输出yes,否则输出no。
Well, we saw the teaser in terms of that animation that suggests this merge sort algorithm when implemented by a computer is absolutely faster.
我们从前面的动画中可以看到,这个归并排序算法在计算机上实现之后,绝对比其他算法更快。
If I'm using algorithm that I'm now calling merge sort, T the running time involved in sorting N elements, T of N, you know, is just the same as running the algorithm for the right half, plus what's this plus N come from?
如果我用归并排序算法,对N个元素其运行时间,就等于此算法一半元素的运行时间,另一半的运行时间,再加上N,这个N是什么呢?
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