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Showing below up to 100 results in range #51 to #150.
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- 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 (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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
- 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)
