Parallel Algorithms: Concepts, Patterns, and Practice

As modern processors pack more cores, writing sequential code is no longer enough to maximize software performance. This text-based course guides you from the absolute basics of parallel computing to designing, analyzing, and testing efficient parallel algorithms. Through this course, you will: 1. Learn the foundational concepts of concurrency, parallelism, and multi-threading. 2. Understand key parallel patterns like divide-and-conquer, map-reduce, and pipelining. 3. Identify and resolve common concurrency issues such as race conditions and deadlocks. 4. Apply Amdahl's Law to analyze speedup and scalability. 5. Practice your knowledge with structured written quizzes and algorithmic challenges. You will start with core terminology and hardware foundations before exploring parallel design patterns and analyzing performance metrics. This course is designed for beginner programmers and computer science students looking to understand how modern software utilizes multi-core processors, with no advanced parallel programming experience required. Start reading today to unlock the power of parallel execution.