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A-chameleon-square-64x64.png (64 × 64 pixels, file size: 2 KB, MIME type: image/png)
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Date/Time | Thumbnail | Dimensions | User | Comment | |
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current | 16:35, 22 October 2015 | 64 × 64 (2 KB) | Nebaruzdin |
File usage
The following 90 pages use this file:
- Algorithm classification
- Auction algorithm
- Backward substitution
- Bellman-Ford algorithm
- Biconjugate gradient stabilized method (BiCGStab)
- Binary search: Finding the position of a target value within a sorted array
- Block Thomas algorithm
- Boruvka's algorithm
- Breadth-first search (BFS)
- Cholesky decomposition
- Classical orthogonalization method
- Classical point-wise Householder (reflections) method for reducing a matrix to Hessenberg form
- Complete cyclic reduction
- Cooley–Tukey Fast Fourier Transform, radix-2 case
- Cubature rules
- DCSC algorithm for finding the strongly connected components
- Dense matrix-vector multiplication
- Dense matrix multiplication (serial version for real matrices)
- Depth-first search (DFS)
- Dijkstra's algorithm
- Disjoint set union
- Dot product
- Face recognition
- Floyd-Warshall algorithm
- Ford–Fulkerson algorithm
- Forward substitution
- GHS algorithm
- Gabow's edge connectivity algorithm
- Gaussian elimination, compact scheme for tridiagonal matrices, serial variant
- Gaussian elimination, compact scheme for tridiagonal matrices, serial version
- Gaussian elimination with column pivoting
- Gaussian elimination with complete pivoting
- Gaussian elimination with diagonal pivoting
- Gaussian elimination with row pivoting
- Givens method
- Hessenberg QR algorithm as implemented in SCALAPACK
- High Performance Conjugate Gradient (HPCG) benchmark
- Hopcroft–Karp algorithm
- Horners method
- Householder (reflections) method for reducing a complex Hermitian matrix to symmetric tridiagonal form
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form
- Householder (reflections) method for the QR decomposition of a square matrix, real point-wise version
- Householder (reflections) reduction of a matrix to bidiagonal form
- Hungarian algorithm
- Johnson's algorithm
- K-means clustering
- Kaczmarz's algorithm
- Kruskal's algorithm
- LU decomposition via Gaussian elimination
- Lanczos algorithm in exact algorithm (without reorthogonalization)
- Linpack benchmark
- Longest shortest path
- Meet-in-the-middle attack
- Newton's method for systems of nonlinear equations
- Numerical quadrature (cubature) rules on an interval (for a multidimensional cube)
- One step of the dqds algorithm
- Orthogonalization method with reorthogonalization
- Parallel prefix scan algorithm using pairwise summation
- Poisson equation, solving with DFT
- Preflow-Push algorithm
- Prim's algorithm
- Purdom's algorithm
- QR algorithm as implemented in SCALAPACK
- QR algorithm for complex Hermitian matrices as implemented in SCALAPACK
- Repeated Thomas algorithm, pointwise version
- Repeated two-sided Thomas algorithm, pointwise version
- Serial Jacobi (rotations) method for symmetric matrices
- Serial Jacobi (rotations) method with thresholds for symmetric matrices
- Shiloach-Vishkin algorithm for finding the connected components
- Single-qubit transform of a state vector
- Stochastic dual dynamic programming (SDDP)
- Stone doubling algorithm for solving bidiagonal SLAEs
- Stone doubling algorithm for the LU decomposition of a tridiagonal matrix
- Symmetric QR algorithm as implemented in SCALAPACK
- Tarjan's algorithm for finding the bridges of a graph
- Tarjan's biconnected components algorithm
- Tarjan's strongly connected components algorithm
- Tarjan-Vishkin biconnected components algorithm
- The classical Jacobi (rotations) method with pivoting for symmetric matrices
- The serial-parallel summation method
- Thomas algorithm, pointwise version
- Two-qubit transform of a state vector
- Two-sided Thomas algorithm, block variant
- Two-sided Thomas algorithm, pointwise version
- Ullman's algorithm
- Uniform norm of a vector: Real version, serial-parallel variant
- VF2 algorithm
- Vertex connectivity of a graph
- Δ-stepping algorithm
- Algowiki:Levels of classification