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Computer Science
Distributed Systems
Parallel and Distributed Computing
1. Introduction to Parallel and Distributed Computing
2. Parallel Computing Fundamentals
3. Parallel Algorithms and Applications
4. Distributed Computing Fundamentals
5. Time and Coordination in Distributed Systems
6. Replication and Consistency
7. Fault Tolerance in Distributed Systems
8. Distributed Algorithms
9. Large-Scale Data Processing
10. Cloud Computing
11. High-Performance Computing
12. Emerging Paradigms and Technologies
13. Performance Analysis and Optimization
14. Security in Parallel and Distributed Systems
3.
Parallel Algorithms and Applications
3.1.
Sorting Algorithms
3.1.1.
Parallel Merge Sort
3.1.2.
Parallel Quick Sort
3.1.3.
Parallel Radix Sort
3.1.4.
Bitonic Sort
3.1.5.
Sample Sort
3.2.
Matrix Computations
3.2.1.
Matrix Multiplication
3.2.1.1.
Cannon's Algorithm
3.2.1.2.
DNS Algorithm
3.2.1.3.
SUMMA Algorithm
3.2.2.
Matrix Decomposition
3.2.2.1.
LU Decomposition
3.2.2.2.
QR Decomposition
3.2.2.3.
Singular Value Decomposition
3.2.3.
Solving Linear Systems
3.2.3.1.
Gaussian Elimination
3.2.3.2.
Iterative Methods
3.3.
Graph Algorithms
3.3.1.
Graph Traversal
3.3.1.1.
Parallel Breadth-First Search
3.3.1.2.
Parallel Depth-First Search
3.3.2.
Shortest Path Algorithms
3.3.2.1.
Parallel Dijkstra's Algorithm
3.3.2.2.
Floyd-Warshall Algorithm
3.3.3.
Minimum Spanning Tree
3.3.3.1.
Parallel Prim's Algorithm
3.3.3.2.
Parallel Kruskal's Algorithm
3.3.4.
Graph Coloring
3.3.5.
Connected Components
3.4.
Search Algorithms
3.4.1.
Parallel Binary Search
3.4.2.
Parallel Hash Table Operations
3.4.3.
Tree Search Algorithms
3.5.
Numerical Algorithms
3.5.1.
Fast Fourier Transform
3.5.2.
Monte Carlo Methods
3.5.3.
Numerical Integration
3.5.4.
Solving Differential Equations
3.6.
String Algorithms
3.6.1.
Parallel String Matching
3.6.2.
Parallel Suffix Array Construction
3.6.3.
Parallel Longest Common Subsequence
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4. Distributed Computing Fundamentals