Foundations of High-Performance and Parallel Computing

As datasets grow and simulations become more complex, standard desktop computers often lack the power to process workloads efficiently. Transitioning to high-performance computing (HPC) environments allows you to leverage massive computational resources and solve problems that were previously impossible to tackle. This text-based course guides you through the core concepts of parallel computing, cluster architectures, and high-throughput workflows. You will transition from writing basic sequential scripts to understanding how to write, configure, and scale applications across distributed systems. What you'll learn: - Understand foundational HPC terminology, hardware architectures, and the principles of parallel speedup. - Navigate remote cluster environments confidently using the Linux command line and Bash scripting. - Configure and submit computational tasks using modern job schedulers like Slurm. - Apply parallel programming concepts using MPI and OpenMP for shared and distributed memory systems. - Implement containerized workflows to ensure application portability and reproducibility across clusters. - Optimize data processing tasks using parallel libraries to maximize CPU utilization. Starting with essential definitions and cluster navigation, this course builds your knowledge systematically, moving from basic command-line operations to advanced parallelization strategies. It is designed for researchers, scientists, engineers, and developers who have basic programming knowledge and want to scale their work using high-performance systems. Start reading today to unlock the full potential of parallel computing.