AI Summary
[DOCUMENT_TYPE: instructional_content]
**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.