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Showing below up to 50 results in range #131 to #180.
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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)
- 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)
- 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)
- 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)
- 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)
- 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)
