Search results
Results from the WOW.Com Content Network
This image or media file may be available on the Wikimedia Commons as File:Python 3.3.2 reference document.pdf, where categories and captions may be viewed. While the license of this file may be compliant with the Wikimedia Commons, an editor has requested that the local copy be kept too.
The two for-loops (line 7 and line 8) can be executed in parallel. The update of the next frontier (line 10) and the increase of distance (line 11) need to be atomic. Atomic operations are program operations that can only run entirely without interruption and pause. A PRAM Model. However, there are two problems in this simple parallelization.
Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle.
In other words, the subcollection {B, D, F} is an exact cover, since every element is contained in exactly one of the sets B = {1, 4}, D = {3, 5, 6}, or F = {2, 7}.There are no more selected rows at level 3, thus the algorithm moves to the next branch at level 2…
An example of such is the classic merge that appears frequently in merge sort examples. The classic merge outputs the data item with the lowest key at each step; given some sorted lists, it produces a sorted list containing all the elements in any of the input lists, and it does so in time proportional to the sum of the lengths of the input lists.
Batcher's odd–even mergesort [1] is a generic construction devised by Ken Batcher for sorting networks of size O(n (log n) 2) and depth O((log n) 2), where n is the number of items to be sorted.
In computer science, iterative deepening search or more specifically iterative deepening depth-first search [1] (IDS or IDDFS) is a state space/graph search strategy in which a depth-limited version of depth-first search is run repeatedly with increasing depth limits until the goal is found.
The basic idea of the algorithm is this: a depth-first search (DFS) begins from an arbitrary start node (and subsequent depth-first searches are conducted on any nodes that have not yet been found). As usual with depth-first search, the search visits every node of the graph exactly once, refusing to revisit any node that has already been visited.