Parallel Programming Foundations with CUDA, OpenMP, and MPI

As data volumes and computational demands grow, standard sequential programming is no longer enough to maximize modern hardware. Understanding how to leverage multi-core processors and graphics cards is essential for building highly performant applications. This text-based course guides you through the foundational concepts of parallel computing, transitioning you from writing single-threaded programs to developing optimized multi-threaded and distributed systems. You will learn how to divide tasks efficiently and harness the power of both CPUs and GPUs. What you'll learn: - Understand the fundamental principles of parallel architectures, shared memory, and distributed memory systems. - Write multi-threaded CPU applications using OpenMP compiler directives for rapid parallelization. - Develop distributed-memory programs with MPI to enable communication across multiple computing nodes. - Program graphics processors with CUDA to accelerate data-intensive algorithms. - Analyze and optimize parallel code to identify bottlenecks and maximize hardware utilization. - Apply modern C++ execution policies and hybrid programming concepts for cleaner, future-proof code. The course begins with essential terminology and the theoretical foundations of parallel architectures. You will then progress through structured, text-based modules covering OpenMP, MPI, and CUDA, supported by conceptual explanations and clear, step-by-step code walk-throughs. This course is designed for software developers, students, and technology enthusiasts who are new to parallel programming. A basic understanding of C or C++ programming is recommended, but no prior experience with high-performance computing is required. Start reading today to unlock the full processing potential of modern hardware.