What This Document Is
This document comprises the introductory lecture materials – specifically lectures 1 through 3 – for CSE 502, a graduate-level Computer Architecture course at Stony Brook University. It’s designed to lay the foundational understanding for the more complex topics explored throughout the semester. These lecture notes offer a starting point for grasping the core principles and historical context of the field. The material draws upon established concepts and adapts insights from leading researchers in the area.
Why This Document Matters
This resource is invaluable for students enrolled in, or preparing to take, an advanced computer architecture course. It’s particularly helpful at the beginning of the semester to establish a common understanding of key concepts and the evolution of the field. It’s also beneficial for anyone seeking a refresher on the fundamental challenges and shifts in computer architecture design, especially concerning performance limitations and emerging trends. Accessing these notes will help you prepare for deeper dives into specific architectural components and optimization techniques.
Topics Covered
* The evolving landscape of computer architecture and its relationship to computer science.
* Historical shifts in design priorities and underlying assumptions (e.g., power vs. transistor costs).
* Key performance limitations impacting modern processor design ("walls" impacting performance).
* The transition from single-core to multi-core processor architectures.
* A comparative look at processor evolution across different eras.
* The challenges and opportunities presented by increasing core counts.
What This Document Provides
* An overview of the current state and historical trajectory of computer architecture.
* A framework for understanding the trade-offs inherent in architectural design choices.
* Contextualization of current research directions within the broader field.
* Visual aids and diagrams illustrating performance trends and architectural concepts.
* A foundation for understanding the quantitative principles used to evaluate computer systems.
