Категория:Статьи в работе: различия между версиями
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Текущая версия на 15:27, 4 июня 2015
Страницы в категории «Статьи в работе»
Показано 200 страниц из 275, находящихся в данной категории.
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- Backward substitution, locality
- Backward substitution, scalability
- Bellman-Ford, C++, Boost Graph Library
- Bellman-Ford, Java, JGraphT
- Bellman-Ford, Ligra
- Bellman-Ford, locality
- Bellman-Ford, MPI, Graph500
- Bellman-Ford, Nvidia nvGraph
- Bellman-Ford, OpenMP, Stinger
- Bellman-Ford, Python, NetworkX
- Bellman-Ford, scalability
- BFS, C++, Boost Graph Library
- BFS, C++, MPI, Boost Graph Library
- BFS, GAP
- BFS, Java, WebGraph
- BFS, Ligra
- BFS, MPI, Graph500
- BFS, Python, NetworkX
- BFS, Python/C++, NetworKit
- BFS, RCC for CPU
- BFS, RCC for GPU
- BFS, VGL
- BiCGStab, HYPRE
- BiCGStab, MIT
- BiCGStab, NVIDIA AmgX
- Binary search, .NET Framework 2.0
- Binary search, C++
- Binary search, Java
- Binary search, locality
- Binary search, Python
- Binary search, С
- Boruvka's, C++, MPI, Parallel Boost Graph Library
- Boruvka's, locality
- Boruvka's, RCC for CPU
- Boruvka's, RCC for GPU
- Boruvka's, scalability
C
D
- DCSC for finding the strongly connected components, C++, MPI, Parallel Boost Graph Library
- Участник:Demiandr
- Dense matrix multiplication, locality
- Dense matrix multiplication, scalability
- Dense matrix-vector multiplication, locality
- Dense matrix-vector multiplication, scalability
- DFS, C++, Boost Graph Library
- DFS, C++, MPI, Parallel Boost Graph Library
- DFS, Python, NetworkX
- Dijkstra, C++, Boost Graph Library
- Dijkstra, C++, MPI: Parallel Boost Graph Library, 1
- Dijkstra, C++, MPI: Parallel Boost Graph Library, 2
- Dijkstra, Google
- Dijkstra, locality
- Dijkstra, Python
- Dijkstra, Python/C++
- Dijkstra, VGL, pull
- Dijkstra, VGL, push
- Disjoint set union, Boost Graph Library
- Disjoint set union, Java, JGraphT
- Dot product, locality
- Dot product, scalability
F
H
- High Performance Conjugate Gradient (HPCG) benchmark
- HITS, VGL
- Hopcroft–Karp, Java, JGraphT
- Horners, locality
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, locality
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, SCALAPACK
- Householder (reflections) method for the QR decomposition, locality
- Householder (reflections) method for the QR decomposition, SCALAPACK
- Householder (reflections) reduction of a matrix to bidiagonal form, locality
- Householder (reflections) reduction of a matrix to bidiagonal form, SCALAPACK
- HPCG, locality
- HPCG, scalability
- Hungarian, Java, JGraphT
K
- K-means clustering, Accord.NET
- K-means clustering, Apache Mahout
- K-means clustering, Ayasdi
- K-means clustering, CrimeStat
- K-means clustering, ELKI
- K-means clustering, Julia
- K-means clustering, Mathematica
- K-means clustering, MATLAB
- K-means clustering, MLPACK
- K-means clustering, Octave
- K-means clustering, OpenCV
- K-means clustering, R
- K-means clustering, RapidMiner
- K-means clustering, SAP HANA
- K-means clustering, SAS
- K-means clustering, scalability1
- K-means clustering, scalability2
- K-means clustering, scalability3
- K-means clustering, scalability4
- K-means clustering, scikit-learn
- K-means clustering, SciPy
- K-means clustering, Spark
- K-means clustering, Stata
- K-means clustering, Torch
- K-means clustering, Weka
- Kaczmarz's, MATLAB1
- Kaczmarz's, MATLAB2
- Kaczmarz's, MATLAB3
- Kruskal's, C++, Boost Graph Library
- Kruskal's, C++, MPI, Parallel Boost Graph Library
- Kruskal's, Java, JGraphT
- Kruskal's, Python, NetworkX
L
- Lanczos, C++, MPI
- Lanczos, C++, MPI, 2
- Lanczos, C++, MPI, 3
- Lanczos, C, MPI
- Lanczos, MPI, OpenMP
- Linpack benchmark
- Linpack, HPL
- Linpack, locality
- Longest shortest path, Java, WebGraph
- Longest shortest path, Python/C++, NetworKit
- LU decomposition via Gaussian elimination, locality
- LU decomposition via Gaussian elimination, scalability
- LU-разложение методом Гаусса с выбором ведущего элемента по всей матрице
- LU-разложение методом Гаусса с выбором ведущего элемента по главной диагонали
- LU-разложение методом Гаусса с выбором ведущего элемента по столбцу
- LU-разложение методом Гаусса с выбором ведущего элемента по строке
M
N
- Newton's method for systems of nonlinear equations, ALIAS C++
- Newton's method for systems of nonlinear equations, Numerical Mathematics - NewtonLib
- Newton's method for systems of nonlinear equations, Numerical Recipes
- Newton's method for systems of nonlinear equations, parallel1
- Newton's method for systems of nonlinear equations, parallel2
- Newton's method for systems of nonlinear equations, parallel3
- Newton's method for systems of nonlinear equations, PETSc
- Newton's method for systems of nonlinear equations, scalability1
- Newton's method for systems of nonlinear equations, scalability2
- Newton's method for systems of nonlinear equations, scalability3
- Newton's method for systems of nonlinear equations, scalability4
- Newton's method for systems of nonlinear equations, Sundials
- Numerical quadrature (cubature) rules on an interval (for a multidimensional cube), scalability
P
- PageRank, VGL
- Pairwise summation of numbers, locality
- Pairwise summation of numbers, scalability
- Poisson equation, solving with DFT, AccFFT
- Poisson equation, solving with DFT, cuFFT
- Poisson equation, solving with DFT, FFTE
- Poisson equation, solving with DFT, FFTW
- Poisson equation, solving with DFT, MKL FFT
- Poisson equation, solving with DFT, P3DFFT
- Poisson equation, solving with DFT, PFFT
- Poisson equation, solving with DFT, scalability
- Preflow-Push, C++, Boost Graph Library
- Preflow-Push, Python, NetworkX
- Prim's, C++, Boost Graph Library
- Prim's, Java, JGraphT
- Purdom's, Boost Graph Library
Q
S
T
- Tarjan's biconnected components, C++, Boost Graph Library
- Tarjan's biconnected components, Java, JGraphT
- Tarjan's biconnected components, Python, NetworkX
- Tarjan's strongly connected components, C++, Boost Graph Library
- Tarjan's strongly connected components, Java, JGraphT
- Tarjan's strongly connected components, Java, WebGraph
- Tarjan's strongly connected components, Python, NetworkX
- Tarjan's strongly connected components, Python/C++, NetworKit
- Tarjan-Vishkin biconnected components, scalability
- The serial-parallel summation method, locality
- The serial-parallel summation method, scalability
- Thomas algorithm, locality
- Thomas, locality
- Two-sided Thomas, locality
