The book Parallel Computing and Architecture provides a comprehensive introduction to the principles, models, and techniques of modern parallel computing. It begins with the fundamentals of computer architecture, distinguishing between architecture and organization, and explains the growing need for parallelism in solving complex computational problems. Various memory architectures such as shared, distributed, and hybrid are discussed along with PRAM models, which form the foundation for parallel algorithm design. The second chapter focuses on multithreading and POSIX threads, exploring thread creation, synchronization using mutexes and semaphores, and performance evaluation through efficiency, redundancy, utilization, and Amdahl’s law. It also introduces static and dynamic interconnection networks that facilitate processor communication. Chapter three presents pipelining as a key performance enhancement strategy, covering arithmetic and instruction pipelines, their stages, hazards, and advanced concepts like vector and superscalar processing, along with cache optimization techniques. The book then examines different parallel architectures under Flynn’s taxonomy, including SIMD, MIMD, multithreaded, systolic, and vector designs, highlighting their advantages, limitations, and real-world applications. Parallel algorithms form the core of Chapter five, where strategies for prefix sums, matrix multiplication, quicksort, and solving linear systems are presented, with emphasis on algorithm analysis, scalability, and cost. The final chapter introduces OpenMP for parallel implementation, detailing directives, work-sharing constructs, synchronization methods, runtime functions, and timing routines. Overall, the book blends theoretical foundations with practical approaches, making it a valuable resource for students, educators, and practitioners seeking to understand parallel computing concepts and their application in high-performance architectures.