Information Package / Course Catalogue
EE 486 Computing with Emerging Technologies
MEF University
Degree Programs
Electrical and Electronics Engineering
General Information For Students
Diploma SupplementErasmus Policy Statement
Electrical and Electronics Engineering
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 EE 486
Course Title in English Computing with Emerging Technologies
Course Title in Turkish Gelişen Teknolojilerle Hesaplama
Language of Instruction EN
Type of Course Flipped Classroom
Level of Course Intermediate
Semester Fall
Contact Hours per Week
Lecture: 3 Recitation: 0 Lab: 0 Other: 0
Estimated Student Workload 153 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites EE 201 - Circuit Analysis I | EE 212 - Electrical and Electronic Circuits
Co-requisites None
Expected Prior Knowledge EE 201 or EE 212
Registration Restrictions Only Undergraduate Students
Overall Educational Objective To learn to understand and analyze emerging nanoelectronic circuits and computing paradigms, compare them with conventional CMOS-based technologies, and investigate related algorithms and CAD tools, so as to explore and innovate in the field of advanced electronic circuits.
Course Description As current CMOS based technologies are approaching their anticipated limits, emerging nanotechnologies and new computing paradigms are expected to be used in future electronic circuits. This course overviews nanoelectronic circuits in a comparison with those of conventional CMOS-based. Deterministic and probabilistic emerging computing models as well as related algorithms and CAD tools are investigated. Regarding the interdisciplinary nature of emerging technologies, this course is appropriate for engineering students with a basic knowledge in circuits.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) compare CMOS circuit elements with circuit elements and devices in computational nanoelectronics including nano-crossbar and memristor switches, reversible quantum gates, approximate circuits and systems, and emerging transistors;
2) simulate emerging computing models and algorithms in circuit level;
3) analyze deterministic and probabilistic computing paradigms;
4) discuss performance of the computing models regarding area, power, speed, and accuracy;
5) apply fault analysis and tolerance techniques for permanent and transient faults.
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3) An ability to communicate effectively with a range of audiences
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics N
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors N
3) An ability to communicate effectively with a range of audiences N
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts N
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives N
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions N
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies N
Prepared by and Date TUBA AYHAN ,
Course Coordinator TUBA AYHAN
Semester Fall
Name of Instructor

Course Contents

Week Subject
1) Introduction
2) Overview of emerging nanoscale devices and switches
3) Reversible quantum computing
4) Reversible circuit analysis and synthesis
5) Molecular computing with individual molecules and DNA strand displacement
6) Computing and logic synthesis with switching nano arrays
7) Nano arrays and memristor arrays
8) Probabilistic/Stochastic and approximate computing
9) Probabilistic/Stochastic and approximate computing
10) Defects, faults, errors, and their analysis and tolerance
11) Defects, faults, errors, and their analysis and tolerance
12) Project design and student presentations
13) Project design and student presentations
14) Project design and student presentations
15) Final examination and presentation period
16) Final examination and presentation period
Required/Recommended Readings1. Adamatzky, A. (Ed.). (2016). Advances in Unconventional Computing: Volume 1: Theory (Vol. 22). Springer. 2. Waser, R. (2012). Nanoelectronics and information technology. John Wiley & Sons. 3. Iniewski, K. (2010). Nanoelectronics: nanowires, molecular electronics, and nanodevices. McGraw Hill Professional. 4. Stanisavljević, M., Schmid, M, Leblebici, Y. (2010). Reliability of Nanoscale Circuits and Systems: Methodologies and Circuit Architectures, Springer. 5. Adamatzky, A., Bull, L., Costello, B. L., Stepney, S., Teuscher, C. (2007). Unconventional Computing, Luniver Press. 6. Zomaya, Y. (2006). Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies, Springer. 7. Yanushkevich, S., Shmerko, V., Lyshevski, S. (2005). Logic Design of NanoICs, CRC Press.
Teaching MethodsContact hours using “Flipped Classroom” as an active learning technique.
Homework and ProjectsPresentations are made individually or in groups depending on class size. Presentation topics will be posted.
Laboratory Work-
Computer UseCircuit CAD tools are used.
Other Activities-
Assessment Methods
Assessment Tools Count Weight
Homework Assignments 4 % 40
Presentation 1 % 20
Project 1 % 40
TOTAL % 100
Course Administration altunm@mef.edu.tr
-
Instructor’s office and phone number: 5th Floor

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
Presentations / Seminar 1 15 2 17
Project 1 30 2 2 34
Homework Assignments 4 6 2 32
Total Workload 153
Total Workload/25 6.1
ECTS 6