Chapter 3: Core Algorithmic Paradigms & Parallel Computing
Chapter 3: Core Algorithmic Paradigms & Parallel Computing
The recurring strategies behind efficient algorithms: divide and conquer, greedy, dynamic programming, backtracking, amortized analysis, and concurrency and parallel computing.
- Divide-and-Conquer & Advanced Sorting (Quick, Merge, Radix, Counting Sort)
- Greedy Choice Paradigms & Interval Scheduling
- Dynamic Programming (Memoization, Tabulation, State Compression, Space Optimization, Peak/Tail Optimization)
- Backtracking, Branch-and-Bound, and Constraint Satisfaction Problems
- Amortized Analysis Techniques (Aggregate, Accounting, and Potential Methods)
- Concurrency & Parallel Computing: Mutexes, Semaphores, Lock-Free CAS Operations, Async Event Loops, and SIMD/Vectorization
- Chapter 3 References