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Showing below up to 284 results in range #51 to #334.
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- Givens (rotations) method for the QR decomposition of a (real) Hessenberg matrix (5 revisions)
- Glossary (5 revisions)
- BFS, Ligra (5 revisions)
- BFS, Python/C++, NetworKit (4 revisions)
- Purdom's, Boost Graph Library (4 revisions)
- Cholesky decomposition, scalability (4 revisions)
- Triangular decomposition of a Gram matrix (4 revisions)
- Gaussian elimination, compact scheme for tridiagonal matrices, serial version (4 revisions)
- Graph connectivity (4 revisions)
- Cholesky decomposition, locality (4 revisions)
- Help (3 revisions)
- Unitary-triangular factorizations (3 revisions)
- Two-sided Thomas algorithm, pointwise version (3 revisions)
- Transitive closure of a directed graph (3 revisions)
- Cooley-Tukey, locality (3 revisions)
- All Pairs Shortest Path (APSP) (3 revisions)
- LU decomposition using Gaussian elimination without pivoting (3 revisions)
- Floyd-Warshall algorithm (3 revisions)
- Shiloach-Vishkin algorithm for finding the connected components (3 revisions)
- Dijkstra, VGL, push (3 revisions)
- Finding maximal flow in a transportation network (3 revisions)
- Search for isomorphic subgraphs (3 revisions)
- Householder (reflections) method for the QR decomposition of a (real) Hessenberg matrix (3 revisions)
- Givens (rotations) method for the QR decomposition of a matrix (3 revisions)
- Tarjan-Vishkin biconnected components algorithm (2 revisions)
- Householder (reflections) method for reducing of a matrix to Hessenberg form (2 revisions)
- Stone doubling algorithm for solving bidiagonal SLAEs (2 revisions)
- Assignment problem (2 revisions)
- Ford–Fulkerson, Java, JGraphT (2 revisions)
- Cholesky decomposition, SCALAPACK (2 revisions)
- Gaussian elimination with row pivoting (2 revisions)
- Householder (reflections) method for the QR decomposition of a matrix (2 revisions)
- Gaussian elimination (finding the LU decomposition) (2 revisions)
- Kruskal's, C++, MPI, Parallel Boost Graph Library (2 revisions)
- BFS, VGL (2 revisions)
- Tarjan's strongly connected components, Java, JGraphT (2 revisions)
- Thomas algorithm, pointwise version (2 revisions)
- Open Encyclopedia of Parallel Algorithmic Features (2 revisions)
- Householder (reflections) method for reducing a complex Hermitian matrix to symmetric tridiagonal form (2 revisions)
- Householder (reflections) reduction of a matrix to bidiagonal form, locality (1 revision)
- Unitary reductions to Hessenberg form (1 revision)
- K-means clustering, SAP HANA (1 revision)
- Floyd-Warshall, C++, Boost Graph Library (1 revision)
- Longest shortest path, Python/C++, NetworKit (1 revision)
- Kaczmarz's, MATLAB3 (1 revision)
- K-means clustering, Spark (1 revision)
- K-means clustering, scalability1 (1 revision)
- Complete cyclic reduction, locality (1 revision)
- Matrix decomposition problem (1 revision)
- Complete cyclic reduction (1 revision)
- Householder (reflections) reduction of a matrix to bidiagonal form, SCALAPACK (1 revision)
- Symmetric QR algorithm as implemented in SCALAPACK (1 revision)
- Householder (reflections) reduction of a matrix to bidiagonal form (1 revision)
- Boruvka's, RCC for CPU (1 revision)
- Bellman-Ford, Java, JGraphT (1 revision)
- Dijkstra, Python/C++ (1 revision)
- DFS, C++, MPI, Parallel Boost Graph Library (1 revision)
- Binary search, Java (1 revision)
- One step of the dqds, LAPACK (1 revision)
- K-means clustering, Torch (1 revision)
- K-means clustering, scalability2 (1 revision)
- Two-sided Thomas, locality (1 revision)
- Hungarian algorithm (1 revision)
- Hopcroft–Karp algorithm (1 revision)
- Disjoint set union (1 revision)
- Fast Fourier transform for powers-of-two (1 revision)
- Biconjugate gradient stabilized method (BiCGStab) (1 revision)
- The Jacobi (rotations) method for solving the symmetric eigenvalue problem (1 revision)
- K-means clustering, Stata (1 revision)
- Johnson's, C++, Boost Graph Library (1 revision)
- Tarjan's biconnected components, Python, NetworkX (1 revision)
- DFS, C++, Boost Graph Library (1 revision)
- Шаблон:Buttonlinkimp (1 revision)
- Poisson equation, solving with DFT, scalability (1 revision)
- GHS algorithm (1 revision)
- K-means clustering, SciPy (1 revision)
- K-means clustering, scalability3 (1 revision)
- Complete cyclic reduction, scalability (1 revision)
- Meet-in-the-middle attack (1 revision)
- Preflow-Push algorithm (1 revision)
- Newton's method for systems of nonlinear equations (1 revision)
- Gaussian elimination with diagonal pivoting (1 revision)
- K-means clustering, SAS (1 revision)
- Δ-stepping, Gap (1 revision)
- Kruskal's, Java, JGraphT (1 revision)
- Tarjan's strongly connected components, C++, Boost Graph Library (1 revision)
- Ford–Fulkerson, Python, NetworkX (1 revision)
- Dijkstra, C++, Boost Graph Library (1 revision)
- BiCGStab, MIT (1 revision)
- DCSC for finding the strongly connected components, C++, MPI, Parallel Boost Graph Library (1 revision)
- VF2 algorithm (1 revision)
- Bellman-Ford, locality (1 revision)
- Floyd-Warshall, scalability (1 revision)
- K-means clustering, scalability4 (1 revision)
- Dense matrix multiplication, locality (1 revision)
- Meet-in-the-middle attack, scalability (1 revision)
- Pairwise summation (1 revision)
- Newton's method for systems of nonlinear equations, scalability1 (1 revision)
- Newton's method for systems of nonlinear equations, Numerical Mathematics - NewtonLib (1 revision)
- Hessenberg QR algorithm as implemented in SCALAPACK (1 revision)
- Unitary reductions to tridiagonal form (1 revision)
- K-means clustering, Mathematica (1 revision)
- Floyd-Warshall, Java, JGraphT (1 revision)
- Tarjan's biconnected components, C++, Boost Graph Library (1 revision)
- Poisson equation, solving with DFT, FFTW (1 revision)
- Δ-stepping, C++, MPI, Parallel Boost Graph Library (1 revision)
- HPCG, locality (1 revision)
- Lanczos, MPI, OpenMP (1 revision)
- Boruvka's, locality (1 revision)
- K-means clustering, Octave (1 revision)
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, SCALAPACK (1 revision)
- K-means clustering, scikit-learn (1 revision)
- Cubature rules (1 revision)
- Dense matrix-vector multiplication, scalability (1 revision)
- Newton's method for systems of nonlinear equations, scalability2 (1 revision)
- Repeated two-sided Thomas algorithm, pointwise version (1 revision)
- Stochastic dual dynamic programming (SDDP) (1 revision)
- Compact scheme for Gaussian elimination and its modifications: Tridiagonal matrix (1 revision)
- Bellman-Ford, Ligra (1 revision)
- Ullman's, C++, Chemical Descriptors Library (1 revision)
- DFS, Python, NetworkX (1 revision)
- Preflow-Push, Python, NetworkX (1 revision)
- Dijkstra, C++, MPI: Parallel Boost Graph Library, 1 (1 revision)
- Lanczos, C, MPI (1 revision)
- Dot product, scalability (1 revision)
- Lanczos, C++, MPI, 2 (1 revision)
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, locality (1 revision)
- K-means clustering, OpenCV (1 revision)
- Pairwise summation of numbers, locality (1 revision)
- Ford–Fulkerson algorithm (1 revision)
- Newton's method for systems of nonlinear equations, scalability3 (1 revision)
- Two-qubit transform of a state vector (1 revision)
- QR algorithm for complex Hermitian matrices as implemented in SCALAPACK (1 revision)
- Jacobi (rotations) method for finding singular values (1 revision)
- Bellman-Ford, MPI, Graph500 (1 revision)
- Poisson equation, solving with DFT, P3DFFT (1 revision)
- BiCGStab, HYPRE (1 revision)
- LU decomposition via Gaussian elimination, scalability (1 revision)
- Lanczos, C++, MPI, 3 (1 revision)
- K-means clustering, MLPACK (1 revision)
- LU decomposition via Gaussian elimination, locality (1 revision)
- Johnson's algorithm (1 revision)
- Pairwise summation of numbers, scalability (1 revision)
- Longest shortest path (1 revision)
- Newton's method for systems of nonlinear equations, scalability4 (1 revision)
- Tarjan's biconnected components algorithm (1 revision)
- Lanczos algorithm in exact algorithm (without reorthogonalization) (1 revision)
- Serial-parallel algorithm for the LU decomposition of a tridiagonal matrix (1 revision)
- K-means clustering, MATLAB (1 revision)
- Bellman-Ford, OpenMP, Stinger (1 revision)
- Dijkstra, Python (1 revision)
- Longest shortest path, Java, WebGraph (1 revision)
- Thomas algorithm (1 revision)
- Givens method, locality (1 revision)
- BiCGStab, NVIDIA AmgX (1 revision)
- Bellman-Ford, scalability (1 revision)
- Binary search: Finding the position of a target value within a sorted array (1 revision)
- Backward substitution, locality (1 revision)
- Kruskal's algorithm (1 revision)
- Meet-in-the-middle attack, implementation1 (1 revision)
- Tarjan-Vishkin biconnected components, scalability (1 revision)
- Classical orthogonalization method (1 revision)
- Reducing matrices to compact forms (1 revision)
- Serial Jacobi (rotations) method with thresholds for symmetric matrices (1 revision)
- K-means clustering, RapidMiner (1 revision)
- Bellman-Ford, Nvidia nvGraph (1 revision)
- VF2, C++, Boost Graph Library (1 revision)
- Tarjan's strongly connected components, Java, WebGraph (1 revision)
- Tarjan's strongly connected components, Python, NetworkX (1 revision)
- Boruvka's, C++, MPI, Parallel Boost Graph Library (1 revision)
- Lanczos, C++, MPI (1 revision)
- The serial-parallel summation method, locality (1 revision)
- Binary search, Python (1 revision)
- Single-qubit transform of a state vector, scalability (1 revision)
- Prim's algorithm (1 revision)
- Auction algorithm (1 revision)
- Meet-in-the-middle attack, implementation2 (1 revision)
- High Performance Conjugate Gradient (HPCG) benchmark (1 revision)
- Two-sided Thomas algorithm, block variant (1 revision)
- Numerical quadrature (cubature) rules on an interval (for a multidimensional cube), scalability (1 revision)
- Gaussian elimination with column pivoting (1 revision)
- The classical Jacobi (rotations) method with pivoting for symmetric matrices (1 revision)
- BFS, MPI, Graph500 (1 revision)
- Ullman's, C++, VF Library (1 revision)
- Hopcroft–Karp, Java, JGraphT (1 revision)
- Kruskal's, Python, NetworkX (1 revision)
- Tarjan's strongly connected components, Python/C++, NetworKit (1 revision)
- Dijkstra, C++, MPI: Parallel Boost Graph Library, 2 (1 revision)
- HPCG, scalability (1 revision)
- Dense matrix multiplication, scalability (1 revision)
- K-means clustering, R (1 revision)
- Horners, locality (1 revision)
- K-means clustering, CrimeStat (1 revision)
- Dijkstra, Google (1 revision)
- Face recognition (1 revision)
- Meet-in-the-middle attack, implementation3 (1 revision)
- Newton's method for systems of nonlinear equations, PETSc (1 revision)
- Householder (reflections) method for the QR decomposition, locality (1 revision)
- Householder (reflections) method for the QR decomposition, SCALAPACK (1 revision)
- Uniform norm of a vector: Real version, serial-parallel variant (1 revision)
- HITS, VGL (1 revision)
- Tarjan's biconnected components, Java, JGraphT (1 revision)
- Preflow-Push, C++, Boost Graph Library (1 revision)
- Poisson equation, solving with DFT, cuFFT (1 revision)
- Binary search, С (1 revision)
- The serial-parallel summation method, scalability (1 revision)
- Boruvka's, scalability (1 revision)
- Face recognition, scalability (1 revision)
- Binary search, .NET Framework 2.0 (1 revision)
- Triangular decompositions (1 revision)
- QR algorithm as implemented in SCALAPACK (1 revision)
- Newton's method for systems of nonlinear equations, Numerical Recipes (1 revision)
- Singular value decomposition (finding singular values and singular vectors) (1 revision)
- Numerical quadrature (cubature) rules on an interval (for a multidimensional cube) (1 revision)
- Boruvka's, RCC for GPU (1 revision)
- PageRank, VGL (1 revision)
- Bellman-Ford, Python, NetworkX (1 revision)
- Poisson equation, solving with DFT, FFTE (1 revision)
- SDDP, scalability (1 revision)
- Binary search, locality (1 revision)
- Single-qubit transform of a state vector, locality (1 revision)
- K-means clustering, Accord.NET (1 revision)
- Thomas, locality (1 revision)
- K-means clustering, Apache Mahout (1 revision)
- K-means clustering (1 revision)
- Newton's method for systems of nonlinear equations, Sundials (1 revision)
- Tarjan's strongly connected components algorithm (1 revision)
- Eigenvalue decomposition (finding eigenvalues and eigenvectors) (1 revision)
- Householder (reflections) method for the QR decomposition of a square matrix, real point-wise version (1 revision)
- K-means clustering, Ayasdi (1 revision)
- Disjoint set union, Java, JGraphT (1 revision)
- Dijkstra, VGL, pull (1 revision)
- Floyd-Warshall, Python, NetworkX (1 revision)
- Poisson equation, solving with DFT, MKL FFT (1 revision)
- Binary search, C++ (1 revision)
- Dot product, locality (1 revision)
- K-means clustering, Weka (1 revision)
- Block Thomas algorithm (1 revision)
- Thomas algorithm, locality (1 revision)
- Depth-first search (DFS) (1 revision)
- Stone doubling algorithm (1 revision)
- Newton's method for systems of nonlinear equations, ALIAS C++ (1 revision)
- Vertex connectivity of a graph (1 revision)
- Gabow's edge connectivity algorithm (1 revision)
- Gaussian elimination with complete pivoting (1 revision)
- Serial-parallel method for solving tridiagonal matrices based on the LU decomposition and backward substitutions (1 revision)
- Bellman-Ford, C++, Boost Graph Library (1 revision)
- Prim's, C++, Boost Graph Library (1 revision)
- Poisson equation, solving with DFT, AccFFT (1 revision)
- QR algorithm (1 revision)
- Linpack, HPL (1 revision)
- K-means clustering, ELKI (1 revision)
- Dijkstra, locality (1 revision)
- Kaczmarz's algorithm (1 revision)
- Uniform norm of a vector, locality (1 revision)
- Dense matrix-vector multiplication, locality (1 revision)
- Newton's method for systems of nonlinear equations, parallel1 (1 revision)
- Orthogonalization method with reorthogonalization (1 revision)
- Parallel prefix scan algorithm using pairwise summation (1 revision)
- Classical point-wise Householder (reflections) method for reducing a matrix to Hessenberg form (1 revision)
- Prim's, Java, JGraphT (1 revision)
- Kruskal's, C++, Boost Graph Library (1 revision)
- Poisson equation, solving with DFT, PFFT (1 revision)
- Kaczmarz's, MATLAB1 (1 revision)
- Repeated Thomas, locality (1 revision)
- Linpack, locality (1 revision)
- Ullman's algorithm (1 revision)
- Backward substitution, scalability (1 revision)
- Newton's method for systems of nonlinear equations, parallel2 (1 revision)
- Tarjan's algorithm for finding the bridges of a graph (1 revision)
- Finding minimal-cost flow in a transportation network (1 revision)
- Serial Jacobi (rotations) method for symmetric matrices (1 revision)
- VF2, C++, VF Library (1 revision)
- VF2, Python, NetworkX (1 revision)
- Disjoint set union, Boost Graph Library (1 revision)
- Hungarian, Java, JGraphT (1 revision)
- Ford–Fulkerson, C++, Boost Graph Library (1 revision)
- Kaczmarz's, MATLAB2 (1 revision)
- K-means clustering, Julia (1 revision)
- Poisson equation, solving with DFT, locality (1 revision)
- Участник:VolkovNikita94 (1 revision)
- Repeated two-sided Thomas, locality (1 revision)
- Dense matrix multiplication (1 revision)
- Newton's method for systems of nonlinear equations, parallel3 (1 revision)
