Parallel Computing | Parallel and Distributed

The content covers concepts in parallel and distributed computing, including system architectures, programming models, algorithm strategies, and performance optimization. Key topics include Flynn's taxonomy, multithreading approaches, consistency models, scheduling techniques, GPU utilization, and message-passing libraries like MPI. The documents discuss practical implementations, advantages, and challenges of various models and methods, particularly focusing on scalability, resource efficiency, and computation speed enhancements in solving complex problems through concurrent processing.