Psychology
Bachelor	Length of the Programme: 4	Number of Credits: 240	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF: Level 6

ECTS Course Information Package

School/Faculty/Institute

Faculty of Engineering

Course Code

COMP 206

Course Title in English

Computer Architecture

Course Title in Turkish

Bilgisayar Mimarisi

Language of Instruction

Type of Course

Flipped Classroom

Level of Course

Introductory

Semester

Spring

Contact Hours per Week

Lecture: 3

Recitation: None

Lab: None

Other: None

Estimated Student Workload

159 hours per semester

Number of Credits

6 ECTS

Grading Mode

Standard Letter Grade

Pre-requisites

EE 203 - Digital Systems Design (+Lojik Lab)

Co-requisites

None

Expected Prior Knowledge

Some exposure to C programming language or other high-level computer programming languages. Exposure to digital logic circuit design is a must.

Registration Restrictions

Only Undergraduate Students

Overall Educational Objective

To learn computer organization, memory, i/o subsystems, processor design and latest computer hardware technology trends.

Course Description

This course introduces the basics of the computer organization and architecture, design of processors, main memory, and i/o devices. It also involves understanding the concept of programs as sequences of machine instructions; understanding the relationship between assembly language and machine language; writing programs using assembly languages; understanding the relationship between high-level compiled languages and assembly languages; understanding arithmetic and logical operations with integer operands; understanding floating-point number systems and operations; understanding data path and controller designs; understanding cache structures and virtual memories; understanding and implementing basic pipelining concepts and learning about advanced microarchitecture concepts such as branch prediction and multicore implementations

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) comprehend computer architecture basics, cost-performance trade-offs, design of instruction set architectures
2) synthesize logic components of a smart computer collectively using software tools
3) communicate individual designs with a range of audience
4) write low-level programs using assembly languages, compile it for a given computer architecture
5) comprehend memory hierarchy, apply logic basics to design cache and memory architectures
6) obtain ability to develop input/output and storage subsystems
7) apply probability and statistics in cache, virtual memory and general subsystem design
8) apply the mathematical background and coding skills in a group project to design fairly complicated computer systems;

Program Learning Outcomes/Course Learning Outcomes	1	2	3	4	5	6	7	8
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.
6) Internalization and dissemination of professional ethical standards.
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity.
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.
12) Ability to acquire knowledge independently, and to plan one’s own learning.
13) Demonstration of advanced competence in the clarity and composition of written work and presentations.

Relation to Program Outcomes and Competences

N None	S Supportive	H Highly Related

	Program Outcomes and Competences	Level	Assessed by
1)	Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.	N
2)	Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.	N
3)	Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.	H	Exam,HW,Participation
4)	Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.	N
5)	Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.	N
6)	Internalization and dissemination of professional ethical standards.	N
7)	Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.	N
8)	Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).	N
9)	Recognition, understanding, and respect for the complexity of sociocultural and international diversity.	S	Participation
10)	Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.	S	HW,Participation
11)	Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.	N
12)	Ability to acquire knowledge independently, and to plan one’s own learning.	S	Exam,HW
13)	Demonstration of advanced competence in the clarity and composition of written work and presentations.	H	Exam,HW

Prepared by and Date	BUSE YILMAZ , March 2024
Course Coordinator	BUSE YILMAZ
Semester	Spring
Name of Instructor	Asst. Prof. Dr. BUSE YILMAZ

Course Contents

Week	Subject
1)	Introduction to Computer Architecture
2)	Overview of computer components and their functionality
3)	Assembly language, Instruction Set Architecture (ISA)
4)	RISC and CISC Architectures, Instruction Set Architecture (ISA), MIPS ISA
5)	MIPS ISA, Trade-offs, design challenges for ISAs, comparison of ISAs
6)	Computer arithmetic
7)	Processor Structure and Function & Midterm 1
8)	Pipelining basics
9)	Pipelining basics cont’d, ILP and Superscalar Processors
10)	Memory Systems, Hierarchies and Operations
11)	Memory Systems, Hierarchies and Operations cont’d & Midterm 2
12)	Input/output and storage subsystems
13)	Advanced concepts: Parallel processing & Multicore architectures
14)	Advanced concepts: GPUs
15)	Final Exam/Project/Presentation Period
16)	Final Exam/Project/Presentation Period

Required/Recommended Readings

The Hardware/Software Interface, 5th Edition, David Patterson and John Hennessy, Computer Organization and Architecture (W. Stallings - 10th Edition), Logic & Computer Design Fundamentals, 5/E, M. Morris R. Mano, Charles R. Kime, Tom Martin Computer Organization and Design

Teaching Methods

Lectures/contact hours using ‘flipped classroom’

Homework and Projects

HWs, Quizzes and 1 project

Laboratory Work

Computer Use

Required

Other Activities

none

Assessment Methods

Assessment Tools	Count	Weight
Quiz(zes)	5	% 20
Project	1	% 30
Midterm(s)	2	% 50
TOTAL		% 100

Course Administration

yilmazbuse@mef.edu.tr
+90 212 395 3719
Rules for attendance, late submissions, missing an exam, etc.: Attendance will be collected in the class: failing to attend at least 10* lectures without proper excuse (health report, at most 2 times) will result in a failing grade. *: 9 for the students who have an overlap with another course. If the students are late to the class more than 15 mins, their attendance won’t be counted. Provided that proper documents are presented, each missed midterm by the student will be given the grade of the average of the other assessments related to the exam topics. No make-up exam shall be given. Late submissions are not accepted for quizzes. Late submission for the project will receive 20 %, 30% and 100% penalty for each passing day.

ECTS Student Workload Estimation

Activity	No/Weeks	Hours			Calculation
	No/Weeks per Semester	Preparing for the Activity	Spent in the Activity Itself	Completing the Activity Requirements
Course Hours	14	2	3		70
Project	1	30	3		33
Quiz(zes)	6	1	1		12
Midterm(s)	2	20	2		44
Total Workload					159
Total Workload/25					6.4
ECTS					6