What This Document Is
This document comprises the introductory lectures (1-3) for Stony Brook University’s CSE 502: Graduate Computer Architecture course. It serves as a foundational overview of the field, setting the stage for more in-depth exploration of computer system design and performance. The material presented establishes key concepts and historical context crucial for understanding modern architectural trends. It’s designed to provide a high-level perspective on the evolution of computing and the challenges faced by computer architects.
Why This Document Matters
This material is essential for graduate students beginning their study of computer architecture, as well as professionals seeking a refresher on core principles. It’s particularly valuable at the start of a course or specialization, providing a common understanding of the fundamental issues and trade-offs involved in designing high-performance computing systems. Understanding these introductory concepts will greatly enhance your ability to grasp more advanced topics covered later in the course.
Topics Covered
* The evolving landscape of computer architecture and its relationship to computer science.
* Historical shifts in conventional wisdom regarding performance bottlenecks (power, instruction-level parallelism, memory access).
* Quantitative principles used to evaluate and compare computer system designs.
* The impact of technology trends on architectural choices.
* The emergence of multi-core processors and the challenges they present.
* A historical perspective on uniprocessor performance and its limitations.
* An overview of early processor designs and their evolution.
What This Document Provides
* A broad overview of the key challenges and opportunities in the field of computer architecture.
* A historical context for understanding current architectural trends.
* A framework for thinking about performance evaluation and quantitative design.
* Insights into the factors driving the shift towards multi-core processors.
* A foundation for understanding the complexities of modern computer systems.
* References to seminal work in the field for further exploration.
