ELE 523E: Computational Nanoelectronics

Announcements

• Sept. 17th The course is given in the Bedri Karafakioğlu seminar room (third floor), EEF.

Overview

As current CMOS based technologies are approaching their anticipated limits, emerging nanotechnologies are expected to replace their role in electronic circuits. This course overviews nanoelectronic circuits in a comparison with those of conventional CMOS-based. Deterministic and probobalistic emerging computing models are investigated. Regarding the interdisciplinary nature of emerging technologies, this course is appropriate for graduate students in different majors including electronics engineering, control engineering, computer science, applied physics, and mathematics. No prior course is required; only basic (college-level) knowledge in circuit design and mathematics is assumed. Topics that are covered include:

• Circuit elements and devices in computational nanoelectronics (in comparison with CMOS) including nano-crossbar switches, reversible quantum gates, approximate circuits and systems, and emerging transistors.
• Introduction of emerging computing models in circuit level.
• Analysis and synthesis of deterministic and probabilistic models.
• Performance of the computing models regarding area, power, speed, and accuracy.
• Uncertainty and faults: fault analysis and tolerance techniques for permanent and transient faults.

Syllabus

ELE 523E: Computational Nanoelectronics, CRN: 15371, Mondays 13:30-16:30, Room: Z2 (Ground Floor-EEF), Fall 2016.

Instructor	Mustafa Altun Email: altunmus@itu.edu.tr Tel: 02122856635 Office hours: 14:00 – 15:00 on Tuesdays in Room:3005, EEF (or stop by my office any time)
Grading	Homework: 20% 4 homeworks (5% each) Midterm Exam: 20% The midterm is during the lecture time on 5/12/2016. Presentation: 20% Presentations are made individually or in groups depending on class size. Presentation topics will be posted. Final Project: 40%
Reference Books	Waser, R. (2012). Nanoelectronics and information technology. John Wiley & Sons. Iniewski, K. (2010). Nanoelectronics: nanowires, molecular electronics, and nanodevices. McGraw Hill Professional. Stanisavljević, M., Schmid, M, Leblebici, Y. (2010). Reliability of Nanoscale Circuits and Systems: Methodologies and Circuit Architectures, Springer. Adamatzky, A., Bull, L., Costello, B. L., Stepney, S., Teuscher, C. (2007). Unconventional Computing, Luniver Press. Zomaya, Y. (2006). Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies, Springer. Yanushkevich, S., Shmerko, V., Lyshevski, S. (2005). Logic Design of NanoICs, CRC Press.
Policies	Homeworks are due at the beginning of class. Late homeworks will be downgraded by 20% for each day passed the due date. Collaboration is permitted and encouraged for homeworks, but each collaborator should turn in his/her own answers. The midterm is in closed-notes and closed-books format. Collaboration is not permitted for the final project.

Weekly Course Plan

Date	Topic
Week 1, 19/9/2016	Introduction
Week 2, 26/9/2016	Overview of emerging nanoscale devices and switches
Week 3, 3/10/2016	Reversible quantum computing, reversible circuit analysis and synthesis
Weeks 4, 10/10/2016	Molecular computing with individual molecules and DNA strand displacement
Weeks 5, 17/10/2016	Computing and logic synthesis with switching nano arrays
Week 6, 24/10/2016	Probabilistic/Stochastic computing with random bit streams and probabilistic switches
Weeks 7, 31/10/2016	Approximate computing and Bayesian networks
Week 8, 7/11/2016	HOLIDAY, no class
Week 9, 14/11/2016	Defects, faults, errors, and their analysis
Weeks 10, 21/11/2016	Fault tolerance in nano-crossbar arrays
Week 11, 28/11/2016	Transient fault tolerance: error detecting and correcting
Week 12, 5/12/2016	MIDTERM
Weeks 13, 12/12/2016	Overview of the midterm, the presentation schedule, and the final project
Weeks 14, 19/12/2016	Student presentations
Weeks 15, 26/12/2016	Student presentations

Course Materials

Lecture Slides	Lecture Slides	Homeworks	Presentations & Exams & Projects
W1: Introduction	W6: Probabilistic Computing	Homework 1	Student Presentations
W2: Emerging Computing	W7: Approximate Computing & Bayesian Networks	Homework 2	Midterm
W3: Reversible Quantum Computing	W9: Faults and Their Analysis	Homework 3	Final Project
W4: Molecular Computing	W10-W11: Fault Tolerance for Nano Electronics	Homework 4
W5: Nanoarray based Computing