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14 docs tagged with "graphs"

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A* & Heuristic Search

Dijkstra's algorithm finds the shortest path to every vertex by always expanding the closest

CUDA Graphs

A single kernel launch costs the CPU roughly 3–10 µs of driver-side work, independent of how much the kernel actually does. A pipeline that issues 50 small kernels per iteration can spend more time launching work than the GPU spends computing it, and Streams and Concurrency doesn't fix that — streams reorder and overlap launches, they don't reduce their count. A CUDA graph captures a whole sequence of operations once and replays it as a single launch, collapsing 50 dispatches into one.

Cycle Detection

A cycle is a path that leaves a vertex and, by following edges, returns to it. That definition reads

Forward Pass and Computational Graphs

A neural network is a function composition, layer feeding layer, and the graph of that composition is exactly what gets differentiated to train the network. Writing the forward pass explicitly as a graph of small, primitive operations is what turns "compute gradients" from a calculus exercise into a completely mechanical procedure — this page establishes that graph view before Backpropagation differentiates it.

Minimum Spanning Trees

Given a connected, undirected, weighted graph, a spanning tree picks exactly V - 1 edges that keep

Network Flow

A flow network is a directed graph where every edge has a capacity, one vertex is a source pumping

Shortest Paths

"Shortest" means fewest edges on an unweighted graph and lowest total weight on a weighted one, and

Topological Sort

A topological sort orders the vertices of a directed acyclic graph so every edge points forward —

Traversal: BFS & DFS

Breadth-first and depth-first search both visit every vertex reachable from a start point, in