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  2. Adjacency list - Wikipedia

    en.wikipedia.org/wiki/Adjacency_list

    An adjacency list representation for a graph associates each vertex in the graph with the collection of its neighbouring vertices or edges. There are many variations of this basic idea, differing in the details of how they implement the association between vertices and collections, in how they implement the collections, in whether they include both vertices and edges or only vertices as first ...

  3. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    A decision version of the problem (testing whether some vertex u occurs before some vertex v in this order) is P-complete, [12] meaning that it is "a nightmare for parallel processing". [13]: 189 A depth-first search ordering (not necessarily the lexicographic one), can be computed by a randomized parallel algorithm in the complexity class RNC ...

  4. Parallel breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Parallel_breadth-first_search

    In the example on the left, there are two arrays, C and R. Array C stores the adjacency lists of all nodes. Array R stored the index in C, the entry R[i] points to the beginning index of adjacency lists of vertex i in array C. The CSR is extremely fast because it costs only constant time to access vertex adjacency.

  5. Kosaraju's algorithm - Wikipedia

    en.wikipedia.org/wiki/Kosaraju's_algorithm

    Provided the graph is described using an adjacency list, Kosaraju's algorithm performs two complete traversals of the graph and so runs in Θ(V+E) (linear) time, which is asymptotically optimal because there is a matching lower bound (any algorithm must examine all vertices and edges).

  6. Reachability - Wikipedia

    en.wikipedia.org/wiki/Reachability

    For each vertex we store the list of adjacencies (out-edges) in order of the planarity of the graph (for example, clockwise with respect to the graph's embedding). We then initialize a counter = + and begin a Depth-First Traversal from . During this traversal, the adjacency list of each vertex is visited from left-to-right as needed.

  7. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    Compared to Dijkstra's algorithm, the A* algorithm only finds the shortest path from a specified source to a specified goal, and not the shortest-path tree from a specified source to all possible goals. This is a necessary trade-off for using a specific-goal-directed heuristic. For Dijkstra's algorithm, since the entire shortest-path tree is ...

  8. Today's Wordle Hint, Answer for #1256 on Tuesday, November 26 ...

    www.aol.com/lifestyle/todays-wordle-hint-answer...

    If you’re stuck on today’s Wordle answer, we’re here to help—but beware of spoilers for Wordle 1256 ahead. Let's start with a few hints.

  9. Prim's algorithm - Wikipedia

    en.wikipedia.org/wiki/Prim's_algorithm

    The adjacency matrix distributed between multiple processors for parallel Prim's algorithm. In each iteration of the algorithm, every processor updates its part of C by inspecting the row of the newly inserted vertex in its set of columns in the adjacency matrix. The results are then collected and the next vertex to include in the MST is ...