Course Syllabus
Course: CS 2810
Division: Natural Science and Math
Department: Computer Science & Engineering
Title: Computer Organization & Architecture
Semester Approved: Spring 2020
Five-Year Review Semester: Summer 2025
End Semester: Fall 2025
Catalog Description: This course introduces organization and architecture of computer systems. Topics include assembly language programming, instruction sets, pipelining, and memory systems.
Semesters Offered: Fall, Spring
Credit/Time Requirement: Credit: 3; Lecture: 3; Lab: 0
Prerequisites: CS 2420 (may be taken concurrently)
CS 2700
Justification: This is a first course in computer systems. It is part of the recommended curriculum for computer science majors at Snow College. This course is articulated across USHE as CS 2810
Student Learning Outcomes:
Students will understand characteristics of an instruction set architecture, an assembly language, assembly level machine organization, and performance and compilation issues. They will demonstrate this by doing homework and taking exams.
Students will be able to analyze computer system organization at the assembly language level, implement algorithms in assembly/machine language, and design a computer system at a block level. They will demonstrate this by doing homework and by doing assembly language programming projects.
Content:
The following topics will be covered in this course: Role of performance; Instruction sets and types; Assembly/machine language; Arithmetic; Datapath and control; Pipelining; Memory management; Interfacing and communication.
Key Performance Indicators:
Homework exercises 10 to 20%
Assembly language programming projects 15 to 25%
3-5 examinations 30 to 60%
Comprehensive final examination 15 to 30%
Representative Text and/or Supplies:
D. Patterson and J. Hennessy, Computer Organization & Design: The Hardware/Software Interface, current edition, Morgan Kaufmann
Pedagogy Statement:
This course will be delivered through lecture, class discussions, presentations, and group problem solving.
Instructional Mediums:
Lecture
Maximum Class Size: 30
Optimum Class Size: 20
