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1. 2.2.1. Описание локальности алгоритма
2. 2.2.2. Описание локальности реализации алгоритма
3. 2.2. Описание локальности данных и вычислений
4. Algorithm classification
5. Anton121 Test Buttons
6. Anton121 Test Page
7. BFS, C++, Boost Graph Library
8. BFS, C++, MPI, Boost Graph Library
9. BFS, GAP
10. BFS, Java, WebGraph
11. BFS, Ligra
12. BFS, MPI, Graph500
13. BFS, Python, NetworkX
14. BFS, Python/C++, NetworKit
15. BFS, RCC for CPU
16. BFS, RCC for GPU
17. BFS, VGL
18. Backward substitution, locality
19. Backward substitution, scalability
20. Bellman-Ford, C++, Boost Graph Library
21. Bellman-Ford, Java, JGraphT
22. Bellman-Ford, Ligra
23. Bellman-Ford, MPI, Graph500
24. Bellman-Ford, Nvidia nvGraph
25. Bellman-Ford, OpenMP, Stinger
26. Bellman-Ford, Python, NetworkX
27. Bellman-Ford, locality
28. Bellman-Ford, scalability
29. BiCGStab, HYPRE
30. BiCGStab, MIT
31. BiCGStab, NVIDIA AmgX
32. Binary search, .NET Framework 2.0
33. Binary search, C++
34. Binary search, Java
35. Binary search, Python
36. Binary search, locality
37. Binary search, С
38. Boruvka's, C++, MPI, Parallel Boost Graph Library
39. Boruvka's, RCC for CPU
40. Boruvka's, RCC for GPU
41. Boruvka's, locality
42. Boruvka's, scalability
43. Cholesky decomposition, SCALAPACK
44. Cholesky decomposition, locality
45. Cholesky decomposition, scalability
46. Complete cyclic reduction, locality
47. Complete cyclic reduction, scalability
48. Cooley-Tukey, locality
49. Cooley-Tukey, scalability
50. DCSC for finding the strongly connected components, C++, MPI, Parallel Boost Graph Library
51. DFS, C++, Boost Graph Library
52. DFS, C++, MPI, Parallel Boost Graph Library
53. DFS, Python, NetworkX
54. Dense matrix-vector multiplication, locality
55. Dense matrix-vector multiplication, scalability
56. Dense matrix multiplication, locality
57. Dense matrix multiplication, scalability
58. DevbunovaViliana / Метод главных компонент (PСA)
59. Dijkstra, C++, Boost Graph Library
60. Dijkstra, C++, MPI: Parallel Boost Graph Library, 1
61. Dijkstra, C++, MPI: Parallel Boost Graph Library, 2
62. Dijkstra, Google
63. Dijkstra, Python
64. Dijkstra, Python/C++
65. Dijkstra, VGL, pull
66. Dijkstra, VGL, push
67. Dijkstra, locality
68. Disjoint set union, Boost Graph Library
69. Disjoint set union, Java, JGraphT
70. Dot product, locality
71. Dot product, scalability
72. EM Алгоритм для пуассон трехточечного распределения
73. Face recognition, scalability
74. Floyd-Warshall, C++, Boost Graph Library
75. Floyd-Warshall, Java, JGraphT
76. Floyd-Warshall, Python, NetworkX
77. Floyd-Warshall, scalability
78. Ford–Fulkerson, C++, Boost Graph Library
79. Ford–Fulkerson, Java, JGraphT
80. Ford–Fulkerson, Python, NetworkX
81. GPU
82. Givens method, locality
83. HITS, VGL
84. HPCG, locality
85. HPCG, scalability
86. Hopcroft–Karp, Java, JGraphT
87. Horners, locality
88. Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, SCALAPACK
89. Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, locality
90. Householder (reflections) method for the QR decomposition, SCALAPACK
91. Householder (reflections) method for the QR decomposition, locality
92. Householder (reflections) reduction of a matrix to bidiagonal form, SCALAPACK
93. Householder (reflections) reduction of a matrix to bidiagonal form, locality
94. Hungarian, Java, JGraphT
95. Johnson's, C++, Boost Graph Library
96. K-means clustering, Accord.NET
97. K-means clustering, Apache Mahout
98. K-means clustering, Ayasdi
99. K-means clustering, CrimeStat
100. K-means clustering, ELKI

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