6 895 Theory Of Parallel Systems Sma 5509 Fall 2003

As modern hardware shifts toward multi-core architectures, understanding how to design efficient parallel algorithms is essential for writing high-performance software. This course demystifies the theoretical foundations of parallel systems, breaking down complex mathematical and algorithmic concepts into clear, digestible principles. You will transition from writing sequential code to thinking parallelly, gaining a deep understanding of how parallel languages, scheduling, and hardware architectures interact. You will learn to analyze parallel algorithms, identify concurrency bugs, and design systems that scale efficiently across multiple processors. What you'll learn: - Understand the fundamental terminology of parallel architectures, scheduling, and concurrency. - Analyze parallel algorithms using work-span models and randomized scheduling techniques. - Master synchronization mechanisms, race detection, and how to avoid deadlock. - Explore memory consistency models, cache coherence, and modern lock-free data structures. - Apply load balancing strategies, including work-stealing algorithms, to optimize resource utilization. - Evaluate routing networks and message-routing algorithms used in parallel hardware. The course begins with core definitions and the basic math behind parallel speedup before moving into synchronization, randomized algorithms, and memory models. You will progress through theoretical analysis and conceptual exercises designed to solidify your understanding of concurrent system design. This course is designed for software developers, computer science students, and systems engineers looking to build a strong theoretical foundation in parallel computing. No prior experience with parallel systems is required. Start reading today to unlock the power of modern parallel computing.