High-Performance Computing: Architectures, Parallel Programming, and Intelligent Applications offers a comprehensive exploration of the technologies, architectures, and intelligent applications that shape modern high-performance computing. As computational workloads continue to expand across Artificial Intelligence, Machine Learning, scientific research, engineering, healthcare, finance, climate modeling, and big data analytics, HPC has become essential for solving complex problems rapidly and efficiently.The book introduces the fundamental concepts of HPC, including performance measurement, scalability, speedup, efficiency, parallelism, and workload optimization. It explores modern computing architectures, including multicore and many-core processors, GPUs, heterogeneous systems, shared-memory and distributed-memory architectures, HPC clusters, supercomputers, and emerging exascale platforms. A significant focus is placed on parallel programming and optimization. Readers are introduced to MPI, OpenMP, Pthreads, CUDA, OpenCL, GPU programming, synchronization, communication, load balancing, memory management, and performance optimization techniques. The book also covers distributed computing, cluster scheduling, grid computing, cloud-based HPC, virtualization, containerization, resource management, fault tolerance, and energy-efficient computing. The book further connects HPC with Artificial Intelligence, Distributed AI, and HPC-enabled intelligent applications.